Relevant bibliographies by topics / Breast masses

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Breast masses'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Breast masses"

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Littrup, Peter J., Nebojsa Duric, Mark Sak, et al. "Multicenter Study of Whole Breast Stiffness Imaging by Ultrasound Tomography (SoftVue) for Characterization of Breast Tissues and Masses." Journal of Clinical Medicine 10, no. 23 (2021): 5528. http://dx.doi.org/10.3390/jcm10235528.

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We evaluated whole breast stiffness imaging by SoftVue ultrasound tomography (UST), extracted from the bulk modulus, to volumetrically map differences in breast tissues and masses. A total 206 women with either palpable or mammographically/sonographically visible masses underwent UST scanning prior to biopsy as part of a prospective, HIPAA-compliant multicenter cohort study. The volumetric data sets comprised 298 masses (78 cancers, 105 fibroadenomas, 91 cysts and 24 other benign) in 239 breasts. All breast tissues were segmented into six categories, using sound speed to separate fat from fibr
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Evans, W. Phil. "BREAST MASSES." Radiologic Clinics of North America 33, no. 6 (1995): 1085–108. http://dx.doi.org/10.1016/s0033-8389(22)00645-5.

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Hindle, William H. "Breast masses." Postgraduate Medicine 88, no. 2 (1990): 85–94. http://dx.doi.org/10.1080/00325481.1990.11704698.

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Salem, Yousif, Abber Farhan, and Noof Alshaibani. "Breast tubular adenoma." International Surgery Journal 6, no. 8 (2019): 2985. http://dx.doi.org/10.18203/2349-2902.isj20193349.

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We present a case of a young woman, with no known comorbidities, who presented with bilateral breasts lumps noted 6 months prior to her initial clinic visit. On examination, both breast masses were felt bilaterally. The masses were completely excised, and histopathologic examination confirmed the diagnosis of breast tubular adenoma. This report aimed to present a rare benign breast neoplasm and discuss the challenges in the diagnosis and management of such condition.
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Liberman, Laura, Lauren A. Ernberg, Alexandra Heerdt, et al. "Palpable Breast Masses." American Journal of Roentgenology 175, no. 3 (2000): 779–87. http://dx.doi.org/10.2214/ajr.175.3.1750779.

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Jales, Rodrigo Menezes, Luís Otavio Sarian, Cleisson Fábio Andrioli Peralta, et al. "Complex Breast Masses." Journal of Ultrasound in Medicine 31, no. 4 (2012): 581–87. http://dx.doi.org/10.7863/jum.2012.31.4.581.

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Knaus, Maria E., and Julia E. Grabowksi. "Pediatric Breast Masses." Advances in Pediatrics 68 (August 2021): 195–209. http://dx.doi.org/10.1016/j.yapd.2021.05.006.

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Wen, Hongmei, Tao Xu, Qinhua Huang, Chumiao Zhang, Qi Zhang, and Haiyan Chen. "Nonpalpable breast masses." Medicine 99, no. 50 (2020): e23556. http://dx.doi.org/10.1097/md.0000000000023556.

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Chau, Alec, A. Pat Romilly, and Nils M. Diaz. "Bilateral Breast Masses." Cancer Control 11, no. 4 (2004): 265. http://dx.doi.org/10.1177/107327480401100410.

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Bellejdel, I., O. Lamzouri, H. Taheri, H. Saadi, and A. Mimouni. "ECTOPIC MAMMARY TISSUE IN THE AXILLARY REGION: A CASE REPORT AND DISCUSSION OF DIAGNOSIS AND MANAGEMENT." International Journal of Advanced Research 11, no. 04 (2023): 69–71. http://dx.doi.org/10.21474/ijar01/16621.

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Ectopic breast tissue, or supernumerary breast tissue, is a rare congenital anomaly that can occur along the milk line, extending from the axilla to the groin. Ectopic breast tissue can undergo the same changes as normal breast tissue, including hormonal changes during pregnancy and lactation, as well as the development of benign or malignant tumors. Herein, we present a case of ectopic breast tissue presenting as axillary masses in a young woman. The patient was a 32-year-old woman who presented with two axillary masses that appeared during lactation after her first and second pregnancies, an
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Dissertations / Theses on the topic "Breast masses"

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Khan, Fyzodeen. "Detection of masses in x-ray mammograms /." View online ; access limited to URI, 2003. http://0-wwwlib.umi.com.helin.uri.edu/dissertations/dlnow/3103706.

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Bovis, Keir Jonathan. "An adaptive knowledge-based model for detecting masses in screening mammograms." Thesis, University of Exeter, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.269735.

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von, Lavante Etienne. "Segmentation and sizing of breast cancer masses with ultrasound elasticity imaging." Thesis, University of Oxford, 2009. http://ora.ox.ac.uk/objects/uuid:81225f61-6b83-405b-aed5-17b316ed586a.

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Uncertainty in the sizing of breast cancer masses is a major issue in breast screening programs, as there is a tendency to severely underestimate the sizing of malignant masses, especially with ultrasound imaging as part of the standard triple assessment. Due to this issue about 20% of all surgically treated women have to undergo a second resection, therefore the aim of this thesis is to address this issue by developing novel image analysis methods. Ultrasound elasticity imaging has been proven to have a better ability to differentiate soft tissues compared to standard B-mode. Thus a novel seg
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Rojas, Dominguez Alfonso. "Automated detection, segmentation and classification of breast masses in digitised mammograms." Thesis, University of Liverpool, 2007. http://livrepository.liverpool.ac.uk/375/.

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A method for automatic detection of mammographic masses is presented. As part of this method, an enhancement algorithm is proposed that improves image contrast based on local statistical measures of the mammograms. After enhancement, regions are segmented via thresholding at multiple levels, and a set of features is computed from each of the segmented regions. A region-ranking system is also presented that identifies the regions most likely to represent abnormalities based on the features computed. The method was tested on 57 mammographic images of masses and achieved a sensitivity of 80% at 2
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Jirari, Mohammed. "Computer Aided System For Detecting Masses In Mammograms." Kent State University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=kent1212099614.

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Tortajada, Giménez Meritxell. "Case-level detection of mammographic masses." Doctoral thesis, Universitat de Girona, 2017. http://hdl.handle.net/10803/620783.

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This thesis is focused on the automatic detection of masses in FFDM images by using case-level information which includes bilateral, temporal and/or ipsilateral information. As a first step, FFDM images are preprocessed to improve image quality. A novel enhancement method is applied to compensate the thickness reduction in peripheral edges of the breast. Following, B-Splines image registration with Affine initialisation is used to obtain bilateral and temporal information that is incorporated in the detection stage. Finally, CC/MLO correspondence approach based on using curved epipolar lines i
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Silva, Leandro Augusto da. "Classificação de nódulos mamográficos utilizando um comitê de redes neurais artificiais." Universidade de São Paulo, 2005. http://www.teses.usp.br/teses/disponiveis/3/3142/tde-05092006-203231/.

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Este trabalho apresenta uma nova estratégia computacional para classificar nódulos mamográficos, que podem ser identificados por radiologistas nos exames de mamografia, em benignos ou malignos. Para a realização dos experimentos computacionais, foram utilizados 57 regiões suspeitas de câncer (ROIs) encontrados pelo radiologista nos exames de mamografia. Das 57 ROIs, 37 foram identificadas como nódulos benignos e 20 identificadas como nódulos malignos, após o exame de biópsia. Com base nestas 57 ROIs são aplicadas técnicas de processamento de imagens para extrair determinadas características qu
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Barnabò, Andrea. "Machine learning techniques for mammography applications." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017.

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During this work we will use machine learning and deep learning techniques in order to face up to some medical problems where they can play a basic role. In particular we will apply these algorithms to some mammography issues. The thesis presents three main experiments that are described below. The first one consists of a classification between nipples and non-nipples images. In this part of the work we will build a dataset composed by images belonging to these two classes. The main purpose here will be to build a classifier able to distinguish between nipple and non-nipple images. Several mac
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Cavdarli, Sumeyye. "Deciphering biosynthesis mechanisms of O-acetylated GD2 in breast cancer." Thesis, Lille 1, 2020. http://www.theses.fr/2020LIL1S100.

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Le ganglioside GD2, ré-exprimé dans les cancers d’origine neuro-ectodermique, a été caractérisé comme un antigène oncofetal constituant une cible pour l’immunothérapie. L’anticorps anti-GD2 dinutuximab (Unitixin, TM) a récemment obtenu l’agrément de la Food Drug Administration et de l’Agence Européenne du Médicament pour le traitement des neuroblastomes pédiatriques. Cependant, l’utilisation de cet anticorps se heurte à de forts problèmes de toxicité due à l’expression du GD2 dans les nerfs périphériques sains. La forme O-acétylée du GD2 (OAcGD2) n’est exprimé que dans les tissus cancéreux rep
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SILVA, Luis Claudio de Oliveira. "Método de detecção de massas em mamas densas usando análise de componentes independentes." Universidade Federal do Maranhão, 2017. http://tedebc.ufma.br:8080/jspui/handle/tede/1897.

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Submitted by Rosivalda Pereira (mrs.pereira@ufma.br) on 2017-09-04T18:08:18Z No. of bitstreams: 1 LuisClaudioSilva.pdf: 4393489 bytes, checksum: 5c3cb715bd7992ba1cc5380c1a940f32 (MD5)<br>Made available in DSpace on 2017-09-04T18:08:18Z (GMT). No. of bitstreams: 1 LuisClaudioSilva.pdf: 4393489 bytes, checksum: 5c3cb715bd7992ba1cc5380c1a940f32 (MD5) Previous issue date: 2017-07-27<br>Breast cancer is the second type of cancer that most a ects women in the world, losing only for non melanoma skin cancer. Breast density can hinder the location of masses, especially in early stages. In this w
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Books on the topic "Breast masses"

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Cabral, Thanh M., and Rangaraj M. Rangayyan. Fractal Analysis of Breast Masses in Mammograms. Springer International Publishing, 2012. http://dx.doi.org/10.1007/978-3-031-01654-7.

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Hastie, Trevor. Computer-aided diagnosis of mammographic masses. University of Toronto, Dept. of Statistics, 1996.

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Nyström, Jan-Åke. Kontraktsbrott vid agenturavtal. 2nd ed. Norstedt, 1988.

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Cabral, Thanh M., and Rangaraj M. Rangayyan. Fractual Analysis of Breast Masses: In Mammograms. Morgan & Claypool Publishers, 2012.

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Cabral, Thanh, and Rangaraj Rangayyan. Fractal Analysis of Breast Masses in Mammograms. Springer International Publishing AG, 2012.

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Cabral, Thanh M., and Rangaraj Rangayyan. Fractal Analysis of Breast Masses in Mammograms. Morgan & Claypool Publishers, 2012.

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Investigation of computerized methods for the detection of masses in digital mammography. 1992.

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Kettler, Mark D. Circumscribed Mass: Invasive Cancer. Edited by Christoph I. Lee, Constance D. Lehman, and Lawrence W. Bassett. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190270261.003.0018.

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Most invasive breast cancers present as focal asymmetries, areas of architectural distortion, or irregular masses with indistinct or spiculated margins. Some present as round or oval masses with circumscribed margins; however, most round or oval masses have microlobulated, indistinct, or spiculated margins and may be associated with characteristic malignant calcifications. This chapter, appearing in the section on circumscribed mass, reviews the key clinical and imaging features, differential diagnosis, and management recommendations for invasive breast cancers, which can present as circumscri
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Kettler, Mark D. Large Circumscribed Mass in Young Female. Edited by Christoph I. Lee, Constance D. Lehman, and Lawrence W. Bassett. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190270261.003.0021.

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Fibroepithelial lesions account for the overwhelming majority of solid breast masses affecting women younger than age 20. Nearly all present as self-detected or provider-detected palpable masses. All fibroepithelial lesions are composed of stromal (fibrous) and glandular (epithelial) elements and variable histology. Rapidly growing mobile breast masses in girls or female adolescents may represent juvenile fibroadenomas, which have different but benign histological features when compared to typical fibroadenomas. Benign phyllodes tumors closely resemble usual fibroadenomas and juvenile fibroade
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Kettler, Mark D. Circumscribed Mass: Intramammary Lymph Node. Edited by Christoph I. Lee, Constance D. Lehman, and Lawrence W. Bassett. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190270261.003.0017.

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This chapter, appearing in the section on circumscribed mass, reviews the key clinical and imaging features, differential diagnosis, and management recommendations for intramammary lymph nodes. Benign intramammary lymph nodes are ubiquitous on screening mammography, and whenever it is possible to do so, they should be differentiated from solid masses in order to avoid unnecessary recalls for diagnostic imaging. Three-dimensional tomosynthesis can facilitate the diagnosis of benign intramammary lymph nodes and decrease the number of recalls for supplemental breast imaging. Ultrasound may help i
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Book chapters on the topic "Breast masses"

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Sencha, Alexander N., Elena V. Evseeva, Mikhail S. Mogutov, and Yury N. Patrunov. "Classification of Breast Masses." In Breast Ultrasound. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36502-7_5.

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Harigopal, Malini, Liva Andrejeva, Sonali Lanjewar, and Peter Podany. "Spiculated Masses." In Radiology Pathology Correlations of Breast Lesions. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-65711-5_5.

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Harigopal, Malini, Madhavi Raghu, Ramya Pham, Alexander Rende, Peter Podany, and Liva Andrejeva. "Circumscribed Masses." In Radiology Pathology Correlations of Breast Lesions. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-65711-5_2.

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Sencha, Alexander N., Elena V. Evseeva, Irina A. Ozerskaya, et al. "Classification of Breast Masses." In Imaging of Male Breast Cancer. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06050-7_5.

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Guliato, Denise, and Rangaraj M. Rangayyan. "Classification of Breast Masses." In Modeling and Analysis of Shape with Applications in Computer-aided Diagnosis of Breast Cancer. Springer International Publishing, 2011. http://dx.doi.org/10.1007/978-3-031-79429-2_4.

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Torrents-Barrena, Jordina, Domenec Puig, Maria Ferre, et al. "Breast Masses Identification through Pixel-Based Texture Classification." In Breast Imaging. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07887-8_81.

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Gherardi, Giorgio. "Breast." In Fine-Needle Biopsy of Superficial and Deep Masses. Springer Milan, 2009. http://dx.doi.org/10.1007/978-88-470-1433-6_2.

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Fornage, Bruno D. "Percutaneous Ablation of Breast Masses." In Interventional Ultrasound of the Breast. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-20829-5_21.

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Sheela, M. C., V. Pavithra, Ramya Ramakrishnan, Bhawna Dev, and Sandhya Sundaram. "Papillary Masses of the Breast." In Holistic Approach to Breast Disease. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0035-0_20.

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Singh, Kamaljeet, James Lee, Malini Harigopal, and Liva Andrejeva. "Masses with Indistinct Margins." In Radiology Pathology Correlations of Breast Lesions. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-65711-5_4.

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Conference papers on the topic "Breast masses"

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Lee, Yu-Yu, and Chau-Jian Huang. "Supervised Technique Integrates Deep Learning Models into Tomographic Identification of Breast Masses." In 2024 International Conference on System Science and Engineering (ICSSE). IEEE, 2024. http://dx.doi.org/10.1109/icsse61472.2024.10608990.

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Narváez, Juan J., Pablo Salamea, and Fabián Narváez. "Breast masses classification using a radiomic analysis in contrast-enhanced spectral mammography." In Computer-Aided Diagnosis, edited by Susan M. Astley and Axel Wismüller. SPIE, 2025. https://doi.org/10.1117/12.3047203.

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Boulehmi, Hela, Hela Mahersia, and Kamel Hamrouni. "Breast masses diagnosis using supervised approaches." In 2016 International Image Processing, Applications and Systems (IPAS). IEEE, 2016. http://dx.doi.org/10.1109/ipas.2016.7880134.

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Avanaki, Ali, Kathyrn S. Espig, Albert Xthona, and Tom R. L. Kimpe. "An anthropomorphic model observer for spiculated masses." In Fourteenth International Workshop on Breast Imaging, edited by Elizabeth A. Krupinski. SPIE, 2018. http://dx.doi.org/10.1117/12.2316831.

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Cavalcante, Jéssica Moreira, Mauro Henrique Muniz Goursand, Douglas de Miranda Pires, Paula Clarke, and Fernanda Silveira de Oliveira. "LYMPHOCYTIC MASTOPHATY PRECEDING BILATERAL PRIMARY BREAST LYMPHOMA – CASE REPORT." In Scientifc papers of XXIII Brazilian Breast Congress - 2021. Mastology, 2021. http://dx.doi.org/10.29289/259453942021v31s1011.

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Introduction: Lymphocytic mastopathy is a rare condition, responsible for 1% of all benign breast lesions, commonly associated to autoimmune disorders and diabetes (especially insulin-requiring diabetes). The differential diagnosis may be difficult, since the clinical and imaging aspects can mimic malignant disease. Some authors suggest that lymphocytic mastitis could be a precursor of primary breast lymphoma. However, other studies disagree with such correlation, presenting the mastopathy as a distinct diagnosis, but one of difficult differentiation from lymphoma. To avoid misdiagnosis, an ap
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Zhang, Xiaohua, Ruola Ning, and Dong Yang. "Three dimensional breast masses autodetection in cone beam breast CT." In SPIE Medical Imaging, edited by Nico Karssemeijer and Maryellen L. Giger. SPIE, 2009. http://dx.doi.org/10.1117/12.813860.

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Kehinde, F. M., G. Erhabor, and M. Afolabi. "Breast and Lymph Node Masses; Tuberculous Mastitis or Breast Cancer?" In American Thoracic Society 2024 International Conference, May 17-22, 2024 - San Diego, CA. American Thoracic Society, 2024. http://dx.doi.org/10.1164/ajrccm-conference.2024.209.1_meetingabstracts.a2362.

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"Breast Masses Classification using a Sparse Representation." In 2nd International Workshop on Medical Image Analysis and Description for Diagnosis Systems. SciTePress - Science and and Technology Publications, 2011. http://dx.doi.org/10.5220/0003304300260033.

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Saunders, Jr., Robert S., and Ehsan Samei. "Characterization of breast masses for simulation purposes." In Medical Imaging 2004, edited by Dev P. Chakraborty and Miguel P. Eckstein. SPIE, 2004. http://dx.doi.org/10.1117/12.535946.

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Kim, Seong Tae, Hakmin Lee, Hak Gu Kim, and Yong Man Ro. "ICADx: interpretable computer aided diagnosis of breast masses." In Computer-Aided Diagnosis, edited by Kensaku Mori and Nicholas Petrick. SPIE, 2018. http://dx.doi.org/10.1117/12.2293570.

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Reports on the topic "Breast masses"

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Kinnard, Lisa M. Computer-Aided Detection of Mammographic Masses in Dense Breast Images. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada437718.

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Sahiner, Berkman. Computer-Aided Characterization of Breast Masses on Volumetric Ultrasound Images: An Adjunct to Mammography. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada443058.

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Sahiner, Berkman. Computer-Aided Characterization of Breast Masses on Volumetric Ultrasound Images: An Adjunct to Mammography. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada411300.

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Eisenbrey, John. Analysis of 3D Subharmonic Ultrasound Signals from Patients with Known Breast Masses for Lesion Differentiation. Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada614106.

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Chen, Hui. Diagnostic performance of superb microvascular imaging for breast masses: a systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review Protocols, 2020. http://dx.doi.org/10.37766/inplasy2020.4.0016.

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Eisenbrey, John. Analysis of 3D Subharmonic Ultrasound Signals from Patients with Known Breast Masses for Lesion Differentiation. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada570988.

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LeCarpentier, Gerald L. Characterization of Breast Masses Using a New Method of Ultrasound Contrast Agent Imaging in 3D Mapping of Vascular Anomalies. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada427005.

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LeCarpentier, Gerald. Characterization of Breast Masses Using a New Method of Ultrasound Contrast Agent Imaging in 3D Mapping of Vascular Anomalies. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada412851.

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LeCarpentier, Gerald L. Characterization of Breast Masses Using a new Method of Ultrasound Contract Agent Imaging in 3D Mapping of Vascular Anomalies. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada468994.

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LeCarpentier, Gerald L. Characterization of Breast Masses Using a New Method of Ultrasound Contrast Agent Imaging in 3D Mapping of Vascular Anomalies. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada468996.

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