Relevant bibliographies by topics / Benign neural tumors

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Academic literature on the topic 'Benign neural tumors'

Author: Grafiati
Published: 5 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Benign neural tumors"

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Rodríguez-Peralto, José Luis, Erica Riveiro-Falkenbach, and Rosario Carrillo. "Benign cutaneous neural tumors." Seminars in Diagnostic Pathology 30, no. 1 (2013): 45–57. http://dx.doi.org/10.1053/j.semdp.2012.01.008.

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Thakur, Soma, and Preety Singh. "Benign Neural Tumors: A Clinicopathologic Analysis." International Journal of Medical and Biomedical Studies 8, no. 3 (2024): 228–33. http://dx.doi.org/10.32553/ijmbs.v8i3.2850.

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Background: Benign neural tumors, including schwannomas, neurofibromas, and meningiomas, are non-malignant growths originating from nerve tissues. Despite their benign nature, these tumors can cause significant morbidity due to their location and potential for recurrence, posing challenges in clinical management. Understanding the clinico-pathologic characteristics of these tumors is essential to optimize treatment strategies and improve patient outcomes. Aim: This study aims to analyze the clinical presentations, histopathological features, and surgical outcomes of benign neural tumors, focus
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Preety, Saha, Kumar Amar, Kumar Manish, and Kumar Bariar Naveen. "Benign Neural Tumors: A Clinical and Pathological Study." International Journal of Pharmaceutical and Clinical Research 16, no. 5 (2024): 2318–24. https://doi.org/10.5281/zenodo.13283659.

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This study investigates benign neural tumors through a clinicopathologic analysis of 93 patients treated at Patna Medical College and Hospital from January 2018 to June 2020. The study identifies schwannomas (45.2%) and meningiomas (32.3%) as the most prevalent tumor types, with neurofibromas and ganglioneuromas constituting smaller proportions. Clinical presentations commonly include headaches, seizures, and neurological deficits. MRI was predominantly used for diagnosis, leading to successful surgical resections in the majority of cases, with a low recurrence rate of 7.5%. Histopathological
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Sultana, Zakia, Md Ashikur Rahman Khan, and Nusrat Jahan. "Early Breast Cancer Detection Utilizing Artificial Neural Network." WSEAS TRANSACTIONS ON BIOLOGY AND BIOMEDICINE 18 (March 18, 2021): 32–42. http://dx.doi.org/10.37394/23208.2021.18.4.

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Breast cancer is one of the most dangerous cancer diseases for women in worldwide. A Computeraided diagnosis system is very helpful for radiologist for diagnosing micro calcification patterns earlier and faster than typical screening techniques. Maximum breast cancer cells are eventually form a lump or mass called a tumor. Moreover, some tumors are cancerous and some are not cancerous. The cancerous tumors are called malignant and non-cancerous tumors are called benign. The benign tumors are not dangerous to health. But the unchecked malignant tumors have the ability to spread in other organs
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Chrysomali, Evanthia, Stavros I. Papanicolaou, Nusi P. Dekker, and Joseph A. Regezi. "Benign neural tumors of the oral cavity." Oral Surgery, Oral Medicine, Oral Pathology, Oral Radiology, and Endodontology 84, no. 4 (1997): 381–90. http://dx.doi.org/10.1016/s1079-2104(97)90036-6.

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Sandhya, Kumari Sinha, Ashab Anwer Md., Kumar Tarun, and Prasad Bhadani Punam. "Benign Peripheral Nerve Sheath Tumors: Clinico-Pathological Spectrum Analysis." International Journal of Pharmaceutical and Clinical Research 16, no. 5 (2024): 2883–86. https://doi.org/10.5281/zenodo.13823651.

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<strong>Background:&nbsp;</strong>Benign neural tumors,a heterogenous group of tumour. Although non-cancerous, can present significant clinical challenges due to their location and potential impact on neural function. Understanding their clinico-pathological characteristics is essential for effective diagnosis and management.&nbsp;<strong>Aim:&nbsp;</strong>This study aims to analyze the clinico-pathological morphological spectrum of benign neural tumors to enhance diagnostic accuracy and therapeutic strategies.&nbsp;<strong>Methods:&nbsp;</strong>A total of 45 patients diagnosed with benign n
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Lusk, Michael D., David G. Kline, and Carlos A. Garcia. "Tumors of the Brachial Plexus." Neurosurgery 21, no. 4 (1987): 439–53. http://dx.doi.org/10.1227/00006123-198710000-00001.

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Abstract Over a 17-year period, 56 patients with 57 tumors involving the brachial plexus were operated upon. The 40 neural sheath tumors included 26 neurofibromas, 8 schwannomas, 4 malignant neural sheath tumors, 1 fibrosarcoma, and 1 meningioma. Nine of the neurofibromas were associated with von Recklinghausen's disease (VRD), and 2 others were what was termed regionalized neurofibromatosis characterized by involvement of one limb with extension along the course of one or more plexus elements. Seventeen tumors were not of neural sheath origin; 7 were benign and 10 were metastatic malignant tu
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Nnadozie, Ugochukwu Uzodimma, Uche Valentine Okeke, Charles Chidebele Maduba, et al. "Morphological Pattern of Benign Skin Tumors in a Teaching Hospital in Southeast Nigeria." Annals of African Surgery 21, no. 3 (2024): 76–82. http://dx.doi.org/10.4314/aas.v21i3.2.

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Background: Benign skin tumors are non-malignant neoplasms of skin origin. They are not uncommon and some have the dreaded propensity for malignant transformation. Aim: The aim of this study is to determine the morphological pattern and distribution of benign skin tumors in a tertiary hospital in southeast Nigeria. Methods: This is a retrospective review of all histologically diagnosed benign skin tumors at a teaching hospital in southeast Nigeria between 2009 and 2019. Information was gathered from the patients’ clinical notes and registers on age, sex, region of body involved, and histologic
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Kryukov, A. I., P. A. Sudarev, S. G. Romanenko, et al. "Diagnosis of benign laryngeal tumors using neural network." Russian Bulletin of Otorhinolaryngology 89, no. 3 (2024): 24. http://dx.doi.org/10.17116/otorino20248903124.

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Liberski, Sławomir, and Jarosław Kocięcki. "Neural Tumors of the Eyelids – A Literature Review." Ophthalmology 27, no. 4 (2025): 32–36. https://doi.org/10.5114/oku/203384.

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Eyelid tumors in about 80–95% of cases belong to benign lesions. Because of the complex anatomy of the eyelids and the resulting diversity of potential sites of initiation of the neoplastic process, as well as because of the morphological similarity of the observed lesions, making a correct diagnosis at the initial stage of the diagnostic process is challenging. Neural tumors originating from peripheral nerves and neuroendocrine cells are rare neoplastic lesions of the eyelids. The most common initially benign neural tumors include plexiform neurofibromas, solitary neurofibromas, and schwannom
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Books on the topic "Benign neural tumors"

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Altshuler, David, Jason A. Heth, and Nicholas J. Szerlip. Skull Tumors. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190696696.003.0023.

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The diagnostic and treatment approach for patients with skull lesions begins with a thorough history and physical and careful attention to anatomic localization. The patient’s history and exam findings can inform a preliminary differential diagnosis, which may be broadly divided into benign and malignant processes. Based on a preliminary assessment, appropriate neuro-imaging involving magnetic resonance, computed tomograph, and/or vascular modalities may be pursued. Characteristic image findings may further refine a differential. While conservative management may be indicated for the most assu
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Beltran, Ralph J. Pheochromocytoma. Edited by Kirk Lalwani, Ira Todd Cohen, Ellen Y. Choi, and Vidya T. Raman. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190685157.003.0044.

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Pheochromocytoma is a rare type of neoplasm diagnosed in children. It originates in the adrenal gland and is different from paragangliomas which arise outside the adrenals. Both types of tumors arise from neural crest cells and lead to signs and symptoms related to hypersecretion of catecholamines. Related symptoms include hypertension, tachycardia, episodic headache, sweating, and abdominal pain. These tumors may be associated with multiple endocrine type 2 syndrome, multiple endocrine neoplasia, and von Hippel-Lindau disease, among other hereditary conditions. Pheochromocytomas can be malign
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Soffietti, Riccardo, Hugues Duffau, Glenn Bauman, and David Walker. Neuronal and mixed neuronal–glial tumours. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199651870.003.0008.

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Neuronal and mixed neuronal-glial tumours are rare tumours of the central nervous system that occur more commonly in children. Despite a generally benign course, most tumours cause medically intractable seizures, and have been denominated as ‘long-term epilepsy-associated tumours’. The World Health Organization classification distinguishes nine histological variants: dysplastic gangliocytoma of the cerebellum/Lhermitte–Duclos disease, desmoplastic infantile astrocytoma and ganglioglioma, dysembryoplastic neuroepithelial tumour, gangliocytoma and ganglioglioma, central neurocytoma and extravent
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Jalali, Rakesih, Patrick Y. Wen, and Takamitsu Fujimaki. Meningiomas. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199651870.003.0011.

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Meningiomas are the most common type of primary brain tumour, comprising approximately one-third of all intracranial neoplasms. It is therefore important for all neuro-oncologists to understand the biology and optimal managements of these tumours. The majority of meningiomas are World Health Organization grade I benign tumours, but grade II (atypical) or grade III (anaplastic) tumours are not uncommon. Total surgical removal is the standard of care but may not be feasible if the tumour involves critical structures such as cranial nerves or important blood vessels. Conventional radiation therap
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King, Adele, and Christopher McKee. Anesthetic Management of Pediatric Craniopharyngioma. Edited by Kirk Lalwani, Ira Todd Cohen, Ellen Y. Choi, and Vidya T. Raman. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190685157.003.0045.

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The challenging perioperative management of craniopharyngiomas requires a multidisciplinary team approach. Though histologically benign, craniopharyngiomas are aggressive with local invasion and frequent recurrences. Significant morbidity maybe there at presentation. Treatment can worsen. Common perioperative concerns include hypothalamic dysfunction, tumor size and its effects on intracranial pressure, as well as the close proximity to nearby vessels and neural structures. Optimal anesthetic management includes thorough preoperative evaluation and planning with detailed knowledge of the tumor
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Book chapters on the topic "Benign neural tumors"

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Arslan, Alime Beyza, and Gökalp Çınarer. "Breast Cancer Diagnosis from Histopathological Images of Benign and Malignant Tumors Using Deep Convolutional Neural Networks." In 2nd International Congress of Electrical and Computer Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-52760-9_9.

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"Benign Neural Gastrointestinal Polyps." In Diagnostic Pathology: Soft Tissue Tumors. Elsevier, 2016. http://dx.doi.org/10.1016/b978-0-323-37675-4.50185-x.

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Sumithra M, Shruthi S, SmithiRam, Swathi S, and Deepika T. "MRI Image Classification of Brain Tumor Using Deep Neural Network and Deployment using Web Framework." In Advances in Parallel Computing. IOS Press, 2021. http://dx.doi.org/10.3233/apc210112.

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A brain tumor is a mass or growth of abnormal cells in our brain. Many different types of brain tumors exist. Some brain tumors are noncancerous (benign), and some brain tumors are cancerous (malignant). Brain tumors can begin in your brain (primary brain tumors), or cancer can begin in other parts of your body and spread to your brain (secondary, or metastatic, brain tumors). Brain tumor treatment options depend on the type of brain tumor you have, as well as its size and location. The classification of brain tumors is performed by biopsy, which is not usually conducted before definitive brai
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Bhattacherjee, Aindrila, Sourav Roy, Sneha Paul, Payel Roy, Noreen Kausar, and Nilanjan Dey. "Classification Approach for Breast Cancer Detection Using Back Propagation Neural Network." In Deep Learning and Neural Networks. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0414-7.ch079.

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According to the recent surveys, breast cancer has become one of the major causes of mortality rate among women. Breast cancer can be defined as a group of rapidly growing cells that lead to the formation of a lump or an extra mass in the breast tissue which consequently leads to the formation of tumor. Tumors can be classified as malignant (cancerous) or benign (non-cancerous). Feature selection is an important parameter in determining the classification systems. Machine learning methods are the most commonly used methods among researchers for breast cancer diagnosis. This paper proposes to i
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"Developing Intelligent Systems for Distinguishing Benign and Malignant Tumors." In Intelligent Engineering Systems through Artificial Neural Networks, Volume 16. ASME Press, 2006. http://dx.doi.org/10.1115/1.802566.paper30.

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Bhattacherjee, Aindrila, Sourav Roy, Sneha Paul, Payel Roy, Noreen Kausar, and Nilanjan Dey. "Classification Approach for Breast Cancer Detection Using Back Propagation Neural Network." In Advances in Bioinformatics and Biomedical Engineering. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-8811-7.ch010.

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According to the recent surveys, breast cancer has become one of the major causes of mortality rate among women. Breast cancer can be defined as a group of rapidly growing cells that lead to the formation of a lump or an extra mass in the breast tissue which consequently leads to the formation of tumor. Tumors can be classified as malignant (cancerous) or benign (non-cancerous). Feature selection is an important parameter in determining the classification systems. Machine learning methods are the most commonly used methods among researchers for breast cancer diagnosis. This paper proposes to i
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Srivastava, Mohit, and Manjeet Singh. "Automatic Brain Tumor Detection: A Review." In Artificial Intelligence and Communication Technologies. Soft Computing Research Society, 2022. http://dx.doi.org/10.52458/978-81-955020-5-9-32.

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Brain tumor is a deadly disease and its detection and diagnosis is a primary concern. Human-assisted manual classification results in inaccurate prediction and identification can result from hence we employ computer-aided technology to aid with diagnosis accuracy. Numerous challenges like its position in the brain, tumor type, abnormality of cells, image segmentation, etc. are needed for its cure. After segmentation of MRI images, on the basis of variation found in tumor tissue characteristics, the tumor is mainly divided into 2 categories i.e. malignant and benign. Numerous reviews on Brain T
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Wu, Jiann-Ming, and Chao-Yuan Tien. "Mobile-Aided Breast Cancer Diagnosis by Deep Convolutional Neural Networks." In Research Anthology on Medical Informatics in Breast and Cervical Cancer. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-7136-4.ch044.

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After verifying the capability of deep learning for basic image recognition, this chapter further extends image recognition to App-aided breast cancer diagnosis. Human cancer has been considered as the most important health problem. For medical image recognition of breast cancer, the presented approach is no longer the same as the traditional. It needs no axioms for distinguishing malignant and benign tumors, and no hand-crafted textural descriptors for feature extraction. The goal is to develop a mobile-aided diagnosis system of directly processing raw medical images. It automatically extract
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"Mobile-Aided Breast Cancer Diagnosis by Deep Convolutional Neural Networks." In Advances in Computer and Electrical Engineering. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1554-9.ch006.

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After verifying the capability of deep learning for basic image recognition, this chapter further extends image recognition to App-aided breast cancer diagnosis. Human cancer has been considered as the most important health problem. For medical image recognition of breast cancer, the presented approach is no longer the same as the traditional. It needs no axioms for distinguishing malignant and benign tumors, and no hand-crafted textural descriptors for feature extraction. The goal is to develop a mobile-aided diagnosis system of directly processing raw medical images. It automatically extract
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"Malignant Epithelial Tumors of the Parotid Gland." In Diagnostic Techniques and Therapeutic Strategies for Parotid Gland Disorders. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-5603-0.ch013.

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Cancer of the parotid gland represents about 20% of all parotid tumors. It either occurs “de-novo” or “on top of pleomorphic adenoma.” There is no sex predilection, and the age of developing this cancer is usually above 50 years. Malignant tumors are as varied as their benign counterparts. Certain tumors are “low-grade” (polymorphous low-grade adenocarcinoma, acinic cell carcinoma, epithelial-myoepithelial carcinoma), while others are “high-grade” (salivary duct carcinoma, large cell carcinoma, and small cell carcinoma). The first echelon lymph node (LN) of metastases is the intra- and peri-gl
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Conference papers on the topic "Benign neural tumors"

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Visumathi, J., N. Kalaivani, S. V. Hemanth, K. Balasubramanian, S. Karthikeyan, and G. Amirthayogam. "Optimized Deep Neural Network for Accurate Detection of Malignant and Benign Brain Tumors." In 2024 3rd International Conference on Artificial Intelligence For Internet of Things (AIIoT). IEEE, 2024. http://dx.doi.org/10.1109/aiiot58432.2024.10574692.

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Li, Jing, Ming Fan, Juan Zhang, and Lihua Li. "Discriminating between benign and malignant breast tumors using 3D convolutional neural network in dynamic contrast enhanced-MR images." In SPIE Medical Imaging, edited by Tessa S. Cook and Jianguo Zhang. SPIE, 2017. http://dx.doi.org/10.1117/12.2254716.

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Chambi, Erick Acuña, Daniel Gil Alzamora, and Antonio Angulo Salas. "Ultrasonic Image Processing for the Classification of Benign and Malignant Breast Tumors: Comparative Study of Convolutional Neural Network Architectures." In CITIIC 2023. MDPI, 2025. https://doi.org/10.3390/engproc2025083015.

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Liu, Hsiao-Chuan, Yi-Hong Chou, Chui-Mei Tiu, Chi-Wen Hsieh, Brent Liu, and K. Kirk Shung. "Differentiating malignant from benign breast tumors on acoustic radiation force impulse imaging using fuzzy-based neural networks with principle component analysis." In SPIE Medical Imaging, edited by Tessa S. Cook and Jianguo Zhang. SPIE, 2017. http://dx.doi.org/10.1117/12.2263476.

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Schmidt, Christian, and Heinrich Martin Overhoff. "Deep learning-based classification of breast tumors using selected subregions of lesions in sonograms." In Computer Science Research Notes. University of West Bohemia, Czech Republic, 2024. http://dx.doi.org/10.24132/csrn.3401.26.

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Breast cancer, a prevalent disease among women, demands early detection for better clinical outcomes. While mammography is widely used for breast cancer screening, its limitation in e.g., dense breast tissue necessitates additional diagnostic tools. Ultrasound breast imaging provides valuable tumor information (features) which are used for standardized reporting, aiding in the screening process and precise biopsy targeting. Previous studies have demonstrated that the classification of regions of interest (ROIs), including only the lesion, outperforms whole image classification. Therefore, our
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M. D, Tharun Kumar, Soniya Priyatharsini G., and Geetha S. "Breast Cancer Detection Using Machine Learning Classifier." In The International Conference on scientific innovations in Science, Technology, and Management. International Journal of Advanced Trends in Engineering and Management, 2023. http://dx.doi.org/10.59544/ovzf8018/ngcesi23p140.

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Breast cancer is one of the main causes of cancer death worldwide. Early diagnostics significantly increases the chances of correct treatment and survival, but this process is tedious and often leads to a disagreement between pathologists. The diagnosis is based on the qualification of histopathologist, who will look for abnormal cells. However, if the histopathologist is not well-trained, this may lead to wrong diagnosis. Computer- aided diagnosis systems showed potential for improving the diagnostic accuracy. In this work, we develop the computational approach based on deep convolution neura
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S, Gunasundari, Meenambal S, Tamilselvi S, and Dhanalakshmi R. "Deep Convolution Neural Network in classification of liver tumor as benign or Malignant from Abdominal Computed Tomography." In 2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT). IEEE, 2022. http://dx.doi.org/10.1109/icicict54557.2022.9917986.

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Gomes, Eduarda Silvestre Ribeiro da Costa, Erlan Pércio Lopes Rufino, Luana Cristina Rodrigues de Oliveira Costa, Assíria Maria Santana Santos, Camilla Flach Weinmann, and Lucas Monteiro Barros Nunes. "Sciatic schwannoma: rare case report." In XIII Congresso Paulista de Neurologia. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1516-3180.140.

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Introduction: Schwannoma is the most common benign tumor of the peripheral nerve sheath. They appear in the sheath of the nervous fascicle and are well-defined masses, which allow their dissection of the underlying neural bundle. Sciatic nerve involvement is rare, accounting for less than 1%. Case report: Male, 83. He has had sciatica on the left for 10 months. With progression of pain, VAS of 9 and difficulty to walk for 1 month after admission. On physical examination, a positive tinel sign in the left gluteal region with tactile perception of nodular lesion in sciatic nerve topography. Pres
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Bettega, Ana Laura Ribas Braga, Bryan Alexander Cuervo, Mario Fernando Davila Obando, et al. "Dermatofibroma vulvar: relato de caso." In 47º Congresso da SGORJ e Trocando Ideias XXVI. Zeppelini Editorial e Comunicação, 2023. http://dx.doi.org/10.5327/jbg-2965-3711-2023133s1114.

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Introdução: Os tumores vulvares representam apenas 4% de todas as neoplasias ginecológicas e são o 4º em frequência, depois dos tumores do colo do útero, útero e ovário. 98% de todos os tumores vulvares são benignos e apenas 2% são malignos. No entanto, fazer o diagnóstico correto nem sempre é fácil devido às similaridades patológicas. Este relato de caso de dermatofibroma vulvar pretende contribuir para a identificação e tratamento de possíveis novos casos. Relato de caso: A.S.D.S., mulher de 88 anos, procurou o ambulatório com queixa de lesão e prurido na região vulvar há aproximadamente um
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Bessa, Willian Ramon Barbosa, Rhaylson Silva do Nascimento, Sebastião Emídio Alves Filho, Marcelino Pereira dos Santos Silva, and Francisco Milton Mendes Neto. "Redes Neurais Convolucionais Aplicadas no Diagnóstico do Câncer de Pulmão." In Encontro Unificado de Computação do Piauí. Sociedade Brasileira de Computação, 2021. http://dx.doi.org/10.5753/enucompi.2021.17749.

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Este trabalho apresenta uma análise comparativa da aplicação de diferentes arquitetura de redes neurais convolucionais no diagnóstico do câncer de pulmão. São detalhados três modelos de redes implementados para o diagnóstico da enfermidade, baseados nas arquiteturas ResNet50v2, Xception e rede sequencial. A fim de melhorar a classificação final, propõe-se também o uso de um método baseado em votação. O treinamento e validação das redes se deu com base no conjunto de dados IQ-OTHNCCD da Universidade de Wasit. O modelo baseado em votação apresentou acurácia geral de 92%, sendo capaz de detectar
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