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Journal articles on the topic 'Semi-automatic segmentation algorithm'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Kim, Sewon, Won Bae, Koichi Masuda, Christine Chung, and Dosik Hwang. "Semi-Automatic Segmentation of Vertebral Bodies in MR Images of Human Lumbar Spines." Applied Sciences 8, no. 9 (2018): 1586. http://dx.doi.org/10.3390/app8091586.

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We propose a semi-automatic algorithm for the segmentation of vertebral bodies in magnetic resonance (MR) images of the human lumbar spine. Quantitative analysis of spine MR images often necessitate segmentation of the image into specific regions representing anatomic structures of interest. Existing algorithms for vertebral body segmentation require heavy inputs from the user, which is a disadvantage. For example, the user needs to define individual regions of interest (ROIs) for each vertebral body, and specify parameters for the segmentation algorithm. To overcome these drawbacks, we develo

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Haniff, Nurin Syazwina Mohd, Muhammad Khalis Abdul Karim, Nurul Huda Osman, M. Iqbal Saripan, Iza Nurzawani Che Isa, and Mohammad Johari Ibahim. "Stability and Reproducibility of Radiomic Features Based Various Segmentation Technique on MR Images of Hepatocellular Carcinoma (HCC)." Diagnostics 11, no. 9 (2021): 1573. http://dx.doi.org/10.3390/diagnostics11091573.

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Hepatocellular carcinoma (HCC) is considered as a complex liver disease and ranked as the eighth-highest mortality rate with a prevalence of 2.4% in Malaysia. Magnetic resonance imaging (MRI) has been acknowledged for its advantages, a gold technique for diagnosing HCC, and yet the false-negative diagnosis from the examinations is inevitable. In this study, 30 MR images from patients diagnosed with HCC is used to evaluate the robustness of semi-automatic segmentation using the flood fill algorithm for quantitative features extraction. The relevant features were extracted from the segmented MR

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Duan, Ye, Xiaoling Li, and Yongjian Xi. "Thalamus Segmentation from Diffusion Tensor Magnetic Resonance Imaging." International Journal of Biomedical Imaging 2007 (2007): 1–5. http://dx.doi.org/10.1155/2007/90216.

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We propose a semi-automatic thalamus and thalamus nuclei segmentation algorithm from Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) based on the mean-shift algorithm. Comparing with existing thalamus segmentation algorithms which are mainly based on K-means algorithm, our mean-shift based algorithm is more flexible and adaptive. It does not assume a Gaussian distribution or a fixed number of clusters. Furthermore, the single parameter in the mean-shift based algorithm supports hierarchical clustering naturally.

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Nikesh, P., and G. Raju. "Directional Vector-Based Skin Lesion Segmentation — A Novel Approach to Skin Segmentation." International Journal of Image and Graphics 20, no. 03 (2020): 2050021. http://dx.doi.org/10.1142/s0219467820500217.

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Efficient skin lesion segmentation algorithms are required for computer aided diagnosis of skin cancer. Several algorithms were proposed for skin lesion segmentation. The existing algorithms are short of achieving ideal performance. In this paper, a novel semi-automatic segmentation algorithm is proposed. The fare concept of the proposed is 8-directional search based on threshold for lesion pixel, starting from a user provided seed point. The proposed approach is tested on 200 images from PH2 and 900 images from ISBI 2016 datasets. In comparison to a chosen set of algorithms, the proposed appr

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Gorbatsevich, V., B. Kulgildin, M. Melnichenko, O. Vygolov, and Y. Vizilter. "SEMI-AUTOMATIC CITYSCAPE 3D MODEL RESTORATION USING GENERATIVE ADVERSARIAL NETWORK." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2020 (August 12, 2020): 415–20. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2020-415-2020.

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Abstract. The paper addresses the problem of a city heightmap restoration using satellite view image and some manually created area with 3D data. We propose the approach based on generative adversarial networks. Our algorithm contains three steps: low quality 3D restoration, buildings segmentation using restored model, and high-quality 3D restoration. CNN architecture based on original ResDilation blocks and ResNet is used for steps one and three. Training and test datasets were retrieved from National Lidar Dataset (United States) and the algorithm achieved approximately MSE = 3.84 m on this

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Wei, Yun Tao, and Yi Bing Zhou. "Research on CT Image Segmentation of Computer-Aided Liver Operation." Applied Mechanics and Materials 513-517 (February 2014): 3115–21. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.3115.

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The segmentation of liver using computed tomography (CT) data has gained a lot of importance in the medical image processing field. In this paper, we present a survey on liver segmentation methods and techniques using CT images for liver segmentation. Generally, liver segmentation methods are divided into two main classes, semi-automatic and fully automatic methods, under each of these two categories, several methods, approaches, related issues and problems will be defined and explained. The evaluation measurements and scoring for the liver segmentation are shown, followed by the comparative s

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Rodríguez, Joaquín, Gilberto Ochoa-Ruiz, and Christian Mata. "A Prostate MRI Segmentation Tool Based on Active Contour Models Using a Gradient Vector Flow." Applied Sciences 10, no. 18 (2020): 6163. http://dx.doi.org/10.3390/app10186163.

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Medical support systems used to assist in the diagnosis of prostate lesions generally related to prostate segmentation is one of the majors focus of interest in recent literature. The main problem encountered in the diagnosis of a prostate study is the localization of a Regions of Interest (ROI) containing a tumor tissue. In this paper, a new GUI tool based on a semi-automatic prostate segmentation is presented. The main rationale behind this tool and the focus of this article is facilitate the time consuming segmentation process used for annotating images in the clinical practice, enabling th

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Song, Liu, Ling, and Yue. "Automatic Semi-Global Artificial Shoreline Subpixel Localization Algorithm for Landsat Imagery." Remote Sensing 11, no. 15 (2019): 1779. http://dx.doi.org/10.3390/rs11151779.

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Shoreline mapping using satellite remote sensing images has the advantages of large-scale surveys and high efficiency. However, low spatial resolution, various geometric morphologies and complex offshore environments prevent accurate positioning of the shoreline. This article proposes a semi-global subpixel shoreline localization method that considers utilizing morphological control points to divide the initial artificial shoreline into segments of relatively simple morphology and analyzing the local intensity homogeneity to calculate the intensity integral error. Combined with the segmentatio

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Qi, Yin Cheng, Ting Li, Ming Xiao Xi, Zhen Bing Zhao, and Yin Ping Cai. "An Image Positioning Method of Automatic Random Walker Based on IFS Edge Detection." Applied Mechanics and Materials 599-601 (August 2014): 802–6. http://dx.doi.org/10.4028/www.scientific.net/amm.599-601.802.

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The segmentation method of classical random walker needs to select seed points artificially, and may cause incomplete or inaccurate segmentation. In view of these problems, this paper presents an image positioning method of automatic random walker based on IFS (Intuitionistic Fuzzy Set). IFS edge detection method is used to get the edge information of image, and then the connected domains are found out in image edge using the morphology method. Select the central pixels of each connected domain as seed points for automatic random walker, and then segment the IFS edge image by random walker. Ex

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Sulayman, Nisreen, Moustafa Al-Mawaldi, and Qosai Kanafani. "Semi-automatic detection and segmentation algorithm of saccular aneurysms in 2D cerebral DSA images." Egyptian Journal of Radiology and Nuclear Medicine 47, no. 3 (2016): 859–65. http://dx.doi.org/10.1016/j.ejrnm.2016.03.016.

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Tuncay, V., N. Prakken, P. M. A. van Ooijen, R. P. J. Budde, T. Leiner, and M. Oudkerk. "Semiautomatic, Quantitative Measurement of Aortic Valve Area Using CTA: Validation and Comparison with Transthoracic Echocardiography." BioMed Research International 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/648283.

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Objective. The aim of this work was to develop a fast and robust (semi)automatic segmentation technique of the aortic valve area (AVA) MDCT datasets.Methods. The algorithm starts with detection and cropping of Sinus of Valsalva on MPR image. The cropped image is then binarized and seed points are manually selected to create an initial contour. The contour moves automatically towards the edge of aortic AVA to obtain a segmentation of the AVA. AVA was segmented semiautomatically and manually by two observers in multiphase cardiac CT scans of 25 patients. Validation of the algorithm was obtained

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Xiberta, Pau, Imma Boada, Anton Bardera, and Maria Font-i-Furnols. "A semi-automatic and an automatic segmentation algorithm to remove the internal organs from live pig CT images." Computers and Electronics in Agriculture 140 (August 2017): 290–302. http://dx.doi.org/10.1016/j.compag.2017.06.003.

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Fakhri Ab. Nasir, Ahmad, M. Nordin A Rahman, Nashriyah Mat, A. Rasid Mamat, and Ahmad Shahrizan Abdul Ghani. "Image Pre-Processing Algorithm for Ficus deltoidea Jack (Moraceae) Varietal Recognition: A Repeated Perpendicular Line Scanning Approach." International Journal of Engineering & Technology 7, no. 2.15 (2018): 49. http://dx.doi.org/10.14419/ijet.v7i2.15.11211.

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Image pre-processing task is always the first crucial step in plant species recognition system which is responsible to keep precision of feature measurement process. Some of researchers have developed the image pre-processing algorithm to remove petiole section. However, the algorithm was developed using semi-automatic algorithm which is strongly believed to give an inaccurate feature measurement. In this paper, a new technique of automatic petiole section removal is proposed based on repeated perpendicular petiole length scanning concept. Four phases of petiole removal technique involved are:

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Walicka, A., G. Jóźków, and A. Borkowski. "INDIVIDUAL ROCKS SEGMENTATION IN TERRESTRIAL LASER SCANNING POINT CLOUD USING ITERATIVE DBSCAN ALGORITHM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2 (May 30, 2018): 1157–61. http://dx.doi.org/10.5194/isprs-archives-xlii-2-1157-2018.

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The fluvial transport is an important aspect of hydrological and geomorphologic studies. The knowledge about the movement parameters of different-size fractions is essential in many applications, such as the exploration of the watercourse changes, the calculation of the river bed parameters or the investigation of the frequency and the nature of the weather events. Traditional techniques used for the fluvial transport investigations do not provide any information about the long-term horizontal movement of the rocks. This information can be gained by means of terrestrial laser scanning (TLS). H

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Dury, Richard, Rob Dineen, Anbarasu Lourdusamy, and Richard Grundy. "Semi-automated medulloblastoma segmentation and influence of molecular subgroup on segmentation quality." Neuro-Oncology 21, Supplement_4 (2019): iv14. http://dx.doi.org/10.1093/neuonc/noz167.060.

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Abstract Medulloblastoma is the most common malignant brain tumour in children. Segmenting the tumour itself from the surrounding tissue on MRI scans has shown to be useful for neuro-surgical planning, by allowing a better understanding of the tumour margin with 3D visualisation. However, manual segmentation of medulloblastoma is time consuming, prone to bias and inter-observer discrepancies. Here we propose a semi-automatic patient based segmentation pipeline with little sensitivity to tumour location and minimal user input. Using SPM12 “Segment” as a base, an additional tissue component desc

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Chernina, V. Y., M. E. Pisov, M. G. Belyaev, et al. "Epicardial fat Tissue Volumetry: Comparison of Semi-Automatic Measurement and the Machine Learning Algorithm." Kardiologiia 60, no. 9 (2020): 46–54. http://dx.doi.org/10.18087/cardio.2020.9.n1111.

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Aim To compare assessments of epicardial adipose tissue (EAT) volumes obtained with a semi-automatic, physician-performed analysis and an automatic analysis using a machine-learning algorithm by data of low-dose (LDCT) and standard computed tomography (CT) of chest organs.Material and methods This analytical, retrospective, transversal study randomly included 100 patients from a database of a united radiological informational service (URIS). The patients underwent LDCT as a part of the project “Low-dose chest computed tomography as a screening method for detection of lung cancer and other dise

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GUO, LI, YUNTING ZHANG, ZEWEI ZHANG, DONGYUE LI, and YING LI. "AN IMPROVED RANDOM WALK SEGMENTATION ON THE LUNG NODULES." International Journal of Biomathematics 06, no. 06 (2013): 1350043. http://dx.doi.org/10.1142/s1793524513500435.

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In this paper, we proposed a semi-automatic technique with a marker indicating the target to locate and segment nodules. For the lung nodule detection, we develop a Gabor texture feature by FCM (Fuzzy C Means) segmentation. Given a marker indicating a rough location of the nodules, a decision process is followed by applying an ellipse fitting algorithm. From the ellipse mask, the foreground and background seeds for the random walk segmentation can be automatically obtained. Finally, the edge of the nodules is obtained by the random walk algorithm. The feasibility and effectiveness of the propo

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Li, Bo, Jing Xue, Kaijian Xia, Leyuan Zhou, Pengjiang Qian, and Yizhang Jiang. "An Auto-Contouring Method for Kidney Using a Novel Semi-Supervised Leaning Extreme Learning Machine Method." Journal of Medical Imaging and Health Informatics 11, no. 8 (2021): 2267–73. http://dx.doi.org/10.1166/jmihi.2021.3675.

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Background: Adaptive radiation therapy planning requires contour segmentation of dangerous organs in medical images. However, manual contour rendering is the most time-consuming and laborious work in radiotherap planning. In order to solve this problem, we propose a novel semi-supervised leaning extreme learning machine (SSL-ELM) method to realize abdominal Magnetic Resonance Imaging (MRI) guided Adaptive Radiation Therapy (MR-ART) automatic contour rendering. Method/Material: Our algorithm is based on the assumption that data within the same class are close to each other. We use this heuristi

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Barbedo, J. G. A. "A novel algorithm for semi-automatic segmentation of plant leaf disease symptoms using digital image processing." Tropical Plant Pathology 41, no. 4 (2016): 210–24. http://dx.doi.org/10.1007/s40858-016-0090-8.

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Zhang, Jiehan, Shengyang Jiang, Huajie Xu, Shihua Tong, Chen Lu, and Shaowei Zhuang. "Diagnosis of Coronary Heart Disease by Optical Coherence Tomography Using Random Walk Algorithm." Journal of Medical Imaging and Health Informatics 11, no. 1 (2021): 127–32. http://dx.doi.org/10.1166/jmihi.2021.3521.

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Objective: The objective is to study the diagnosis of coronary heart disease by optical coherence tomography based on random walk algorithm, so as to assist doctors in diagnosing coronary heart disease. Method: K-means algorithm combined with mathematical morphology provides seed points for random walk algorithm, and realizes semi-automatic segmentation of different kinds of patches. Secondly, by adding the space distance term based on the distance between the edge and the seed point in the weight function, the random walk algorithm is improved, which can make the weak edge patch area not be s

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Wissel, Tobias, Patrick Stüber, Benjamin Wagner, Achim Schweikard, and Floris Ernst. "Tissue segmentation from head MRI: a ground truth validation for feature-enhanced tracking." Current Directions in Biomedical Engineering 1, no. 1 (2015): 228–31. http://dx.doi.org/10.1515/cdbme-2015-0057.

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AbstractAccuracy is essential for optical head-tracking in cranial radiotherapy. Recently, the exploitation of local patterns of tissue information was proposed to achieve a more robust registration. Here, we validate a ground truth for this information obtained from high resolution MRI scans. In five subjects we compared the segmentation accuracy of a semi-automatic algorithm with five human experts. While the algorithm segments the skin and bone surface with an average accuracy of less than 0.1 mm and 0.2 mm, respectively, the mean error on the tissue thickness was 0.17 mm. We conclude that

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de la Rosa, Ezequiel, Désiré Sidibé, Thomas Decourselle, Thibault Leclercq, Alexandre Cochet, and Alain Lalande. "Myocardial Infarction Quantification from Late Gadolinium Enhancement MRI Using Top-Hat Transforms and Neural Networks." Algorithms 14, no. 8 (2021): 249. http://dx.doi.org/10.3390/a14080249.

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Late gadolinium enhancement (LGE) MRI is the gold standard technique for myocardial viability assessment. Although the technique accurately reflects the damaged tissue, there is no clinical standard to quantify myocardial infarction (MI). Moreover, commercial software used in clinical practice are mostly semi-automatic, and hence require direct intervention of experts. In this work, a new automatic method for MI quantification from LGE-MRI is proposed. Our novel segmentation approach is devised for accurately detecting not only hyper-enhanced lesions, but also microvascular obstruction areas.

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Gou, Zhi Yang, Sheng Hong Fan, Cong Li, Chang Ru Liu, Meng Wang, and Lai Wei Jiang. "Combined Use of Spectral and Spatial Features for Building Extraction in Multi-Spectral Imagery." Applied Mechanics and Materials 333-335 (July 2013): 1164–70. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.1164.

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As essential character of urban region, building extraction and recognition has been applied broadly in urban mapping, urban planning and population census. Traditional manual plotting is time consuming and expensive, which therefore challenges for automatic or semi-automatic solutions. High-resolution multi-spectral remote sensing imagery provides both spectral and spatial information for acquiring urban features to update geographic information database. An advanced algorithm based on the combined use of spectral and spatial features will be developed and employed to recognize and extract bu

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Martin, M., D. Letourneau, V. Pekar, R. Wong, M. Gospodarowicz, and D. Jaffray. "52 IMPLEMENTATION OF A SEMI-AUTOMATIC VERTEBRA DETECTION AND SEGMENTATION ALGORITHM FOR RADIOTHERAPY OF SPINOUS BONE METASTASES." Radiotherapy and Oncology 92 (September 2009): S17. http://dx.doi.org/10.1016/s0167-8140(12)72439-8.

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Kum, O., and H. Kim. "SU-FF-J-113: Semi-Automatic Segmentation of CT Image Using Watershed Algorithm and Graphical User Interface." Medical Physics 34, no. 6Part6 (2007): 2394. http://dx.doi.org/10.1118/1.2760618.

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Amrehn, Mario, Stefan Steidl, Reinier Kortekaas, et al. "A Semi-Automated Usability Evaluation Framework for Interactive Image Segmentation Systems." International Journal of Biomedical Imaging 2019 (September 5, 2019): 1–21. http://dx.doi.org/10.1155/2019/1464592.

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For complex segmentation tasks, the achievable accuracy of fully automated systems is inherently limited. Specifically, when a precise segmentation result is desired for a small amount of given data sets, semi-automatic methods exhibit a clear benefit for the user. The optimization of human computer interaction (HCI) is an essential part of interactive image segmentation. Nevertheless, publications introducing novel interactive segmentation systems (ISS) often lack an objective comparison of HCI aspects. It is demonstrated that even when the underlying segmentation algorithm is the same throug

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Inage, A. "RIGHT VENTRICULAR VOLUMES AND FUNCTION ASSESSED BY CARDIOVASCULAR MAGNETIC RESONANCE WITH A SEMI-AUTOMATIC THRESHOLD-BASED SEGMENTATION ALGORITHM." Canadian Journal of Cardiology 30, no. 10 (2014): S106. http://dx.doi.org/10.1016/j.cjca.2014.07.125.

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Jia, Hongguo, Bowen Wei, Guoxiang Liu, Rui Zhang, Bing Yu, and Shuaiying Wu. "A Semi-Automatic Method for Extracting Small Ground Fissures from Loess Areas Using Unmanned Aerial Vehicle Images." Remote Sensing 13, no. 9 (2021): 1784. http://dx.doi.org/10.3390/rs13091784.

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Remote sensing-based ground fissure extraction techniques (e.g., image classification, image segmentation, feature extraction) are widely used to monitor geological hazards and large-scale artificial engineering projects such as bridges, dams, highways, and tunnels. However, conventional technologies cannot be applied in loess areas due to their complex terrain, diverse textural information, and diffuse ground target boundaries, leading to the extraction of many false ground fissure targets. To rapidly and accurately acquire ground fissures in the loess areas, this study proposes a data proces

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Cai, Jun, Jian-Zhen Luo, and Fangyuan Lei. "Analyzing Network Protocols of Application Layer Using Hidden Semi-Markov Model." Mathematical Problems in Engineering 2016 (2016): 1–14. http://dx.doi.org/10.1155/2016/9161723.

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With the rapid development of Internet, especially the mobile Internet, the new applications or network attacks emerge in a high rate in recent years. More and more traffic becomes unknown due to the lack of protocol specifications about the newly emerging applications. Automatic protocol reverse engineering is a promising solution for understanding this unknown traffic and recovering its protocol specification. One challenge of protocol reverse engineering is to determine the length of protocol keywords and message fields. Existing algorithms are designed to select the longest substrings as p

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Biratu, Erena Siyoum, Friedhelm Schwenker, Taye Girma Debelee, Samuel Rahimeto Kebede, Worku Gachena Negera, and Hasset Tamirat Molla. "Enhanced Region Growing for Brain Tumor MR Image Segmentation." Journal of Imaging 7, no. 2 (2021): 22. http://dx.doi.org/10.3390/jimaging7020022.

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A brain tumor is one of the foremost reasons for the rise in mortality among children and adults. A brain tumor is a mass of tissue that propagates out of control of the normal forces that regulate growth inside the brain. A brain tumor appears when one type of cell changes from its normal characteristics and grows and multiplies abnormally. The unusual growth of cells within the brain or inside the skull, which can be cancerous or non-cancerous has been the reason for the death of adults in developed countries and children in under developing countries like Ethiopia. The studies have shown th

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Jaspers, Karolien, Hendrik G. Freling, Kees van Wijk, Elisabeth I. Romijn, Marcel J. W. Greuter, and Tineke P. Willems. "Improving the reproducibility of MR-derived left ventricular volume and function measurements with a semi-automatic threshold-based segmentation algorithm." International Journal of Cardiovascular Imaging 29, no. 3 (2012): 617–23. http://dx.doi.org/10.1007/s10554-012-0130-5.

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Lee, Moon Hwan, Jun-Young Kim, Kyungsu Lee, Chang-Hyuk Choi, and Jae Youn Hwang. "Wide-Field 3D Ultrasound Imaging Platform With a Semi-Automatic 3D Segmentation Algorithm for Quantitative Analysis of Rotator Cuff Tears." IEEE Access 8 (2020): 65472–87. http://dx.doi.org/10.1109/access.2020.2985858.

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Moldovan, Flaviu, Adrian Gligor, and Tiberiu Bataga. "Structured Integration and Alignment Algorithm: A Tool for Personalized Surgical Treatment of Tibial Plateau Fractures." Journal of Personalized Medicine 11, no. 3 (2021): 190. http://dx.doi.org/10.3390/jpm11030190.

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The planning of the surgical treatment in orthopedics, with the help of three-dimensional (3D) technologies, arouses an increasing scientific interest. Scientific literature describes some semi-automatic reconstructive attempts at fragmented bone fractures, but the matching algorithms presented are likely to improve. The aim of this paper is to develop a new method of aligning fragments of comminutive fractures. We have created a structured integration process and an alignment algorithm integrated in a clinical workflow for personalized surgical treatment of fractures. The provided solution is

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Dakua, Sarada Prasad. "LV Segmentation Using Stochastic Resonance and Evolutionary Cellular Automata." International Journal of Pattern Recognition and Artificial Intelligence 29, no. 03 (2015): 1557002. http://dx.doi.org/10.1142/s0218001415570025.

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High-level noise and low contrast characteristics in medical images continue to present major bottlenecks in their segmentation despite increased imaging modalities. This paper presents a semi-automatic algorithm that utilizes the noise for enhancing the contrast of low contrast input magnetic resonance images followed by a new graph cut method to reconstruct the surface of left ventricle. The main contribution in this work is a new formulation for preventing the conventional cellular automata method to leak into surrounding regions of similar intensity. Instead of segmenting each slice of a s

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Gentillon, Hugues, Ludomir Stefańczyk, Michał Strzelecki, and Maria Respondek-Liberska. "Prenatal brain MRI samples for development of automatic segmentation, target- recognition and machine-learning algorithms to detect anatomical structures." F1000Research 6 (January 31, 2017): 93. http://dx.doi.org/10.12688/f1000research.10723.1.

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In this data note, we present a sorted pool of fetal magnetic resonance imaging (MRI) specimens, selected for a project seeking to further develop a computer-vision software called MaZda, originally created for magnetic resonance (MR) image analysis. A link to download the samples is provided in the manuscript herein. This data descriptor further explains how and why these fetal MRI samples were selected. Firstly, thousands of cross-sectional images obtained from fetal MRI scans were processed and sorted semi-manually with other software. We did so because a built-in “samplesort” (sorting algo

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Gentillon, Hugues, Ludomir Stefańczyk, Michał Strzelecki, and Maria Respondek-Liberska. "Prenatal brain MRI samples for development of automatic segmentation, target-recognition, and machine-learning algorithms to detect anatomical structures." F1000Research 6 (September 8, 2017): 93. http://dx.doi.org/10.12688/f1000research.10723.2.

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In this data note, we present a sorted pool of fetal magnetic resonance imaging (MRI) specimens. These were selected for a project seeking to further develop computer vision software called MaZda, which was originally created for magnetic resonance (MR) image analysis. A link to download the samples is provided in the manuscript herein. This data descriptor further explains how and why these fetal MRI samples were selected. Firstly, thousands of cross-sectional images obtained from fetal MRI scans were processed and sorted semi-manually with other software. We did so because a built-in “sample

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Asmussen, Pascal, Olaf Conrad, Andreas Günther, Moritz Kirsch, and Ulrich Riller. "Semi-automatic segmentation of petrographic thin section images using a “seeded-region growing algorithm” with an application to characterize wheathered subarkose sandstone." Computers & Geosciences 83 (October 2015): 89–99. http://dx.doi.org/10.1016/j.cageo.2015.05.001.

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Cui, Weihong, Guofeng Wang, Chenyi Feng, Yiwei Zheng, Jonathan Li, and Yi Zhang. "SPMK AND GRABCUT BASED TARGET EXTRACTION FROM HIGH RESOLUTION REMOTE SENSING IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 21, 2016): 195–203. http://dx.doi.org/10.5194/isprs-archives-xli-b7-195-2016.

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Target detection and extraction from high resolution remote sensing images is a basic and wide needed application. In this paper, to improve the efficiency of image interpretation, we propose a detection and segmentation combined method to realize semi-automatic target extraction. We introduce the dense transform color scale invariant feature transform (TC-SIFT) descriptor and the histogram of oriented gradients (HOG) & HSV descriptor to characterize the spatial structure and color information of the targets. With the k-means cluster method, we get the bag of visual words, and then, we ado

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Mikula, Karol, Mária Šibíková, Martin Ambroz, et al. "NaturaSat—A Software Tool for Identification, Monitoring and Evaluation of Habitats by Remote Sensing Techniques." Remote Sensing 13, no. 17 (2021): 3381. http://dx.doi.org/10.3390/rs13173381.

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The NaturaSat software integrates various image processing techniques together with vegetation data, into one multipurpose tool that is designed for performing facilities for all requirements of habitat exploration, all in one place. It provides direct access to multispectral Sentinel-2 data provided by the European Space Agency. It supports using these data with various vegetation databases, in a user-friendly environment, for, e.g., vegetation scientists, fieldwork experts, and nature conservationists. The presented study introduces the NaturaSat software, describes new powerful tools, such

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Zhao, Yifei, Fenzhen Su, and Fengqin Yan. "Novel Semi-Supervised Hyperspectral Image Classification Based on a Superpixel Graph and Discrete Potential Method." Remote Sensing 12, no. 9 (2020): 1528. http://dx.doi.org/10.3390/rs12091528.

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Hyperspectral image (HSI) classification plays an important role in the automatic interpretation of the remotely sensed data. However, it is a non-trivial task to classify HSI accurately and rapidly due to its characteristics of having a large amount of data and massive noise points. To address this problem, in this work, a novel, semi-supervised, superpixel-level classification method for an HSI was proposed based on a graph and discrete potential (SSC-GDP). The key idea of the proposed scheme is the construction of the weighted connectivity graph and the division of the weighted graph. Based

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Budha, P. B., and A. Bhardwaj. "LANDSLIDE EXTRACTION FROM SENTINEL-2 IMAGE IN SIWALIK OF SURKHET DISTRICT, NEPAL." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-5/W2 (December 5, 2019): 9–15. http://dx.doi.org/10.5194/isprs-annals-iv-5-w2-9-2019.

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Abstract. Locating landslides and determining its extent is deemed an important task in estimating loss and damage and carry out mitigation works. As landslides are recurring phenomena in the research site, Siwalik Hills of western Nepal, freely available Sentinel-2 satellite images were considered to delineate landslides. The method employed in this process was Object-Based Image Analysis carried out in eCognition software using multiresolution segmentation algorithm. Parameters taken for segmentation were a scale of 20, the shape of 0.3, and compactness of 0.5. When a threshold value of <

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Can, R., S. Kocaman, and A. O. Ok. "A WEBGIS FRAMEWORK FOR SEMI-AUTOMATED GEODATABASE UPDATING ASSISTED BY DEEP LEARNING." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B5-2021 (June 30, 2021): 13–19. http://dx.doi.org/10.5194/isprs-archives-xliii-b5-2021-13-2021.

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Abstract. The automation of geoinformation (GI) collection and interpretation has been a fundamental goal for many researchers. The developments in various sensors, platforms, and algorithms have been contributing to the achievement of this goal. In addition, the contributions of citizen science (CitSci) and volunteered geographical information (VGI) concepts have become evident and extensive for the geodata collection and interpretation in the era where information has the utmost importance to solve societal and environmental problems. The web- and mobile-based Geographical Information System

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Iantsen, Andrei, Marta Ferreira, Francois Lucia, et al. "Convolutional neural networks for PET functional volume fully automatic segmentation: development and validation in a multi-center setting." European Journal of Nuclear Medicine and Molecular Imaging 48, no. 11 (2021): 3444–56. http://dx.doi.org/10.1007/s00259-021-05244-z.

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Abstract Purpose In this work, we addressed fully automatic determination of tumor functional uptake from positron emission tomography (PET) images without relying on other image modalities or additional prior constraints, in the context of multicenter images with heterogeneous characteristics. Methods In cervical cancer, an additional challenge is the location of the tumor uptake near or even stuck to the bladder. PET datasets of 232 patients from five institutions were exploited. To avoid unreliable manual delineations, the ground truth was generated with a semi-automated approach: a volume

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Martin-Gonzalez, Teresa, Graeme Penney, Debra Chong, Meryl Davis, and Tara M. Mastracci. "Accuracy of implementing principles of fusion imaging in the follow up and surveillance of complex aneurysm repair." Vascular Medicine 23, no. 5 (2018): 461–66. http://dx.doi.org/10.1177/1358863x18768885.

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Fusion imaging is standard for the endovascular treatment of complex aortic aneurysms, but its role in follow up has not been explored. A critical issue is renal function deterioration over time. Renal volume has been used as a marker of renal impairment; however, it is not reproducible and remains a complex and resource-intensive procedure. The aim of this study is to determine the accuracy of a fusion-based software to automatically calculate the renal volume changes during follow up. In this study, computerized tomography (CT) scans of 16 patients who underwent complex aortic endovascular r

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Johansson, A. Malin, Eirik Malnes, Sebastian Gerland, et al. "Consistent ice and open water classification combining historical synthetic aperture radar satellite images from ERS-1/2, Envisat ASAR, RADARSAT-2 and Sentinel-1A/B." Annals of Glaciology 61, no. 82 (2020): 40–50. http://dx.doi.org/10.1017/aog.2019.52.

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AbstractSynthetic Aperture Radar (SAR) satellite images are used to monitor Arctic sea ice, with systematic data records dating back to 1991. We propose a semi-supervised classification method that separates open water from sea ice and can utilise ERS-1/2, Envisat ASAR, RADARSAT-2 and Sentinel-1 SAR images. The classification combines automatic segmentation with a manual segment selection stage. The segmentation algorithm requires only the backscatter intensities and incidence angle values as input, therefore can be used to establish a consistent decadal sea ice record. In this study we invest

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Santucci, Domiziana, Eliodoro Faiella, Ermanno Cordelli, et al. "3T MRI-Radiomic Approach to Predict for Lymph Node Status in Breast Cancer Patients." Cancers 13, no. 9 (2021): 2228. http://dx.doi.org/10.3390/cancers13092228.

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Background: axillary lymph node (LN) status is one of the main breast cancer prognostic factors and it is currently defined by invasive procedures. The aim of this study is to predict LN metastasis combining MRI radiomics features with primary breast tumor histological features and patients’ clinical data. Methods: 99 lesions on pre-treatment contrasted 3T-MRI (DCE). All patients had a histologically proven invasive breast cancer and defined LN status. Patients’ clinical data and tumor histological analysis were previously collected. For each tumor lesion, a semi-automatic segmentation was per

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Luo, Bachagha, Yao, et al. "Identifying Linear Traces of the Han Dynasty Great Wall in Dunhuang Using Gaofen-1 Satellite Remote Sensing Imagery and the Hough Transform." Remote Sensing 11, no. 22 (2019): 2711. http://dx.doi.org/10.3390/rs11222711.

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The Han Dynasty Great Wall (GH), one of the largest and most significant ancient defense projects in the whole of northern China, has been studied increasingly not only because it provides important information about the diplomatic and military strategies of the Han Empire (206 B.C.–220 A.D.), but also because it is considered to be a cultural and national symbol of modern China as well as a valuable archaeological monument. Thus, it is crucial to obtain the spatial pattern and preservation situation of the GH for next-step archaeological analysis and conservation management. Nowadays, remote

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Garrido-González, C., M. L. Ladehesa Pineda, J. L. Garrido-Castro, et al. "POS0958 RESPONSIVENESS OF CONVENTIONAL, SEMI-AUTOMATIC AND FULL-AUTOMATIC METHODS TO QUANTIFY MARROW BONE EDEMA LESIONS IN MRI OF AXIAL SPONDYLOARTHRITIS PATIENTS: A PILOT STUDY." Annals of the Rheumatic Diseases 80, Suppl 1 (2021): 743.2–744. http://dx.doi.org/10.1136/annrheumdis-2021-eular.864.

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Background:The presence or absence of marrow bone edema (MBE) in the sacroiliac joints (SIJ) is very important in the diagnosis of axial Spondyloarthritis (axSpA). The quantification of this lesion and its extension may be important to analyze responsiveness of the treatment. Several scoring systems have been proposed for MRI images of SIJ, some of them being observer dependent (Berlin, SPARCC). Others, works in a semi-automatically way, such as the s-SCAISS[1], which makes it possible to quantify the size of the lesion, based on the indication of the expert. Recently, methods like the KITs4R[

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Coelho-Silva, Fernanda, Luciano Augusto Cano Martins, Daniela Azeredo Braga, Eliana Zandonade, Francisco Haiter-Neto, and Sergio Lins de-Azevedo-Vaz. "Influence of windowing and metal artefact reduction algorithms on the volumetric dimensions of five different high-density materials: a cone-beam CT study." Dentomaxillofacial Radiology 49, no. 8 (2020): 20200039. http://dx.doi.org/10.1259/dmfr.20200039.

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Objective: To assess the influence of windowing and metal artefact reduction (MAR) algorithms on the volumetric dimensions of high-density materials using two CBCT systems. Methods: Four cylinders of amalgam, cobalt-chromium, gutta-percha, titanium and zirconium, were manufactured and their physical volumes (PV) were measured. A polymethyl methacrylate phantom containing the cylinders was submitted to CBCT acquisitions with Picasso Trio and OP300 units with their MAR enabled and disabled. The tomographic volume (TV) of all the cylinders was obtained by semi-automatic segmentation using two win

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Zahra, Qoseen, Muhammad Sheraz Arshad Malik, and Naila Batool. "An Efficient Computer-Aided Diagnosis System for the Analysis of DICOM Volumetric Images." July 2019 38, no. 3 (2019): 835–50. http://dx.doi.org/10.22581/muet1982.1903.24.

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Medical images are an important source of diagnosis. The brain of human analysis is now an advanced field of research for computer scientists and biomedical physicians. Services provided by the healthcare units usually vary, the quality of treatment provided in the urban and rural generally not same. Unavailability of medical equipment and services can have serious consequences in patient disease diagnosis and treatment. In this context, we developed. MRI (Magnetic Resonance Imaging) based CAD (Computer Aided Diagnosis) system which takes MRI as input and detects abnormal tissues (Tumors). MRI

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