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1Dissertation/ Thesis
المؤلفون: Yu, Xiang
مصطلحات موضوعية: Automatic, Breast mass detection, Mammogram, classification, Deep Learning (DL), Computing and Mathematical Sciences, thesis
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2Academic Journal
المؤلفون: Seo, Jae Won, Kim, Young Jae, Park, Chang Min, Jin, Kwang Nam, Kim, Kwang Gi
المساهمون: Park, Chang Min
مصطلحات موضوعية: Breast, Mammography, Computer, aided diagnosis, Breast mass detection, Artificial intelligence
Relation: Progress in Biomedical Optics and Imaging - Proceedings of SPIE, Vol.12926, p. 129262P; https://hdl.handle.net/10371/208847; 001223523300083; 2-s2.0-85193494368; 217104
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3Academic Journal
المؤلفون: Sajida Imran, Bilal Ahmed Lodhi, Ali Alzahrani
المصدر: IEEE Access, Vol 9, Pp 99327-99338 (2021)
مصطلحات موضوعية: Breast mass detection, automatic mammogram segmentation, mass classification, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
وصف الملف: electronic resource
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4Book
المؤلفون: Kassahun R. K., Molinara M., Bria A., Marrocco C., Tortorella F.
المساهمون: Kassahun, R. K., Molinara, M., Bria, A., Marrocco, C., Tortorella, F.
مصطلحات موضوعية: Breast Cancer, Breast Mass Classification, Breast Mass Detection, Computer Aided Diagnosi, RadImageNet, Transfer Learning, YOLO ObjectDetection
Relation: info:eu-repo/semantics/altIdentifier/isbn/9783031510250; info:eu-repo/semantics/altIdentifier/isbn/9783031510267; ispartofbook:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); volume:14366; firstpage:71; lastpage:82; numberofpages:12; serie:LECTURE NOTES IN COMPUTER SCIENCE; https://hdl.handle.net/11580/107425; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85184126203
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5Academic Journal
المؤلفون: Lilei Sun, Huijie Sun, Junqian Wang, Shuai Wu, Yong Zhao, Yong Xu
المصدر: Sensors; Volume 21; Issue 8; Pages: 2855
مصطلحات موضوعية: medical image processing, mammographic image, deep learning, breast mass detection
وصف الملف: application/pdf
Relation: Physical Sensors; https://dx.doi.org/10.3390/s21082855
الاتاحة: https://doi.org/10.3390/s21082855
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6Academic Journal
المؤلفون: Min, Hang, Chandra, Shekhar S., Crozier, Stuart, Bradley, Andrew P.
المصدر: Biomedical Physics and Engineering Express
مصطلحات موضوعية: breast mass detection and segmentation, cascaded random forest, ensemble learning, mammography, morphological sifting
وصف الملف: application/pdf
Relation: https://eprints.qut.edu.au/197689/1/43273353.pdf; Min, Hang, Chandra, Shekhar S., Crozier, Stuart, & Bradley, Andrew P. (2019) Multi-scale sifting for mammographic mass detection and segmentation. Biomedical Physics and Engineering Express, 5(2), Article number: 025022 1-15.; https://eprints.qut.edu.au/197689/
الاتاحة: https://eprints.qut.edu.au/197689/
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7Academic Journal
مصطلحات موضوعية: рак молочної залози, згорткові нейронні мережі, YOLO, Inception-V3, виявлення пухлин молочної залози, класифікація пухлин молочної залози, breast cancer, convolutional neural networks, breast mass detection, breast mass classification, 004.81 + 616-006
وصف الملف: Pp. 52-61; application/pdf
Relation: Біомедична інженерія і технологія, № 10; Соколенко, О. Виявлення та класифікація пухлин молочної залози з використанням глибинного навчання / Соколенко Ольга Віталіївна, Данілова Валентина Анатоліївна // Біомедична інженерія і технологія. – 2023. – № 10. – С. 52-61. – Бібліогр.: 21 назва.; https://ela.kpi.ua/handle/123456789/58425; https://doi.org/10.20535/2617-8974.2023.10.281430; orcid:0009-0007-7514-6249; orcid:0000-0003-3009-6421
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8
مصطلحات موضوعية: breast cancer, breast mass classification, convolutional neural networks, 004.81 + 616-006, YOLO, виявлення пухлин молочної залози, рак молочної залози, класифікація пухлин молочної залози, згорткові нейронні мережі, Inception-V3, breast mass detection
وصف الملف: application/pdf
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9Book
المؤلفون: Min, Hang, Chandra, Shekhar, Dhungel, Neeraj, Crozier, Stuart, Bradley, Andrew
المساهمون: Egan, G, Salvado, O
المصدر: Proceedings of the 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)
مصطلحات موضوعية: Average sensitivities, Breast mass detection, Cascade of random forests, Class imbalance, Decision trees, False positive, Image segmentation, Mammography, Mass segmentation, Medical imaging, Morphological filtering, Segmentation, andom forests
وصف الملف: application/pdf
Relation: https://eprints.qut.edu.au/114136/2/114136.pdf; Min, Hang, Chandra, Shekhar, Dhungel, Neeraj, Crozier, Stuart, & Bradley, Andrew (2017) Multi-scale mass segmentation for mammograms via cascaded random forests. In Egan, G & Salvado, O (Eds.) Proceedings of the 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017). Institute of Electrical and Electronics Engineers Inc., United States of America, pp. 113-117.; https://eprints.qut.edu.au/114136/; Science & Engineering Faculty
الاتاحة: https://eprints.qut.edu.au/114136/
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10
المؤلفون: Huijie Sun, Yong Zhao, Junqian Wang, Yong Xu, Shuai Wu, Lilei Sun
المصدر: Sensors, Vol 21, Iss 2855, p 2855 (2021)
Sensors (Basel, Switzerland)
Sensors
Volume 21
Issue 8مصطلحات موضوعية: Computer science, Image processing, Breast Neoplasms, 02 engineering and technology, TP1-1185, Mathematical morphology, Biochemistry, Convolutional neural network, medical image processing, Article, 030218 nuclear medicine & medical imaging, Analytical Chemistry, 03 medical and health sciences, 0302 clinical medicine, Breast cancer, Minimum bounding box, 0202 electrical engineering, electronic engineering, information engineering, medicine, Mammography, Humans, Breast, Electrical and Electronic Engineering, mammographic image, skin and connective tissue diseases, Instrumentation, Early Detection of Cancer, medicine.diagnostic_test, business.industry, Template matching, Chemical technology, Particle swarm optimization, deep learning, Pattern recognition, medicine.disease, Atomic and Molecular Physics, and Optics, breast mass detection, Radiographic Image Interpretation, Computer-Assisted, 020201 artificial intelligence & image processing, Artificial intelligence, Neural Networks, Computer, business, Algorithms
وصف الملف: application/pdf
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11Conference
المؤلفون: Jun Zhang, EH Cain, A Saha, Z Zhu, MA Mazurowski
مصطلحات موضوعية: Breast mass detection, fully convolutional network, Life Sciences & Biomedicine, mammography, Optics, Physical Sciences, Radiology, Nuclear Medicine & Medical Imaging, Science & Technology, tomosynthesis, transfer learning
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12
المؤلفون: Ali Alzahrani, Bilal Ahmed Lodhi, Sajida Imran
المصدر: IEEE Access, Vol 9, Pp 99327-99338 (2021)
Bilal Lodhiمصطلحات موضوعية: FOS: Computer and information sciences, General Computer Science, Computer science, Computer Vision and Pattern Recognition (cs.CV), Population, Feature extraction, Computer Science - Computer Vision and Pattern Recognition, Breast cancer, mass classification, medicine, Mammography, General Materials Science, education, education.field_of_study, automatic mammogram segmentation, Receiver operating characteristic, medicine.diagnostic_test, business.industry, General Engineering, Pattern recognition, Image segmentation, medicine.disease, Breast mass detection, Hierarchical clustering, TK1-9971, Identification (information), Artificial intelligence, Electrical engineering. Electronics. Nuclear engineering, business
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13Dissertation/ Thesis
المؤلفون: Xiang Yu
مصطلحات موضوعية: Uncategorized, Automatic, Breast mass detection, Mammogram, classification, Deep Learning (DL), Computing and Mathematical Sciences, thesis
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14Book
المؤلفون: Dhungel, Neeraj, Carneiro, Gustavo, Bradley, Andrew
المساهمون: Unal, G, Wells, W, Sabuncu, M R, Ourselin, S, Joskowicz, L
المصدر: Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016: 19th International Conference, Proceedings, Part II (Lecture Notes in Computer Science, Volume 9901)
مصطلحات موضوعية: Artificial intelligence, Breast mass, Breast mass classification, Breast mass detection, Classification (of information), Classification performance, Classification results, Deep learning, Learning systems, Machine learning models, Mammograms, Mammography, Medical imaging, Texture information, X ray screens
Relation: Dhungel, Neeraj, Carneiro, Gustavo, & Bradley, Andrew (2016) The automated learning of deep features for breast mass classification from mammograms. In Unal, G, Wells, W, Sabuncu, M R, Ourselin, S, & Joskowicz, L (Eds.) Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016: 19th International Conference, Proceedings, Part II (Lecture Notes in Computer Science, Volume 9901). Springer, Switzerland, pp. 106-114.; https://eprints.qut.edu.au/114156/; Science & Engineering Faculty
الاتاحة: https://eprints.qut.edu.au/114156/
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15Academic Journal
المؤلفون: Petrick, Nicholas, Chan, Heang‐ping, Sahiner, Berkman, Helvie, Mark A.
المساهمون: The University of Michigan, Department of Radiology, CGC B2102, 1500 East Medical Center Drive, Ann Arbor, Michigan 48109â 0904
مصطلحات موضوعية: cancer, Mammography, Medical imaging, Physicists, Image analysis, densityâ weight contrast enhancement, region growing, computerâ aided diagnosis, digital mammography, breast mass detection, image segmentation, medical image processing, Medicine (General), Health Sciences
وصف الملف: application/pdf
Relation: Petrick, Nicholas; Chan, Heang‐ping; Sahiner, Berkman; Helvie, Mark A. (1999). "Combined adaptive enhancement and regionâ growing segmentation of breast masses on digitized mammograms." Medical Physics 26(8): 1642-1654.; https://hdl.handle.net/2027.42/134789; Medical Physics; Y. L. Chang and X. Li, â Adaptive image regionâ growing,â IEEE Trans. Image Process. IIPRE4 --> 3, 868 â 872 ( 1994 ).; L. Tabar et al., â Reduction in mortality from breast cancer after mass screening with mammography,â Lancet LANCAO --> 1, 829 â 832 ( 1985 ).; E. L. Thurfjell, K. A. Lernevall, and A. A. S. Taube, â Benefit of independent double reading in a populationâ based mammography screening program,â Radiology RADLAX --> 191, 241 â 244 ( 1994 ).; C. J. Vyborny and M. L. Giger, â Computer vision and artificial intelligence in mammography,â AJR, Am. J. Roentgenol. AAJRDX --> 162, 699 â 708 ( 1994 ).; N. Karssemeijer and G. te Brake, â Detection of stellate distortions in mammograms,â IEEE Trans. Med. Imaging ITMID4 --> 15, 611 â 619 ( 1996 ).; H. Kobatake and Y. Yoshinaga, â Detection of spicules on mammogram based on skeleton analysis,â IEEE Trans. Med. Imaging ITMID4 --> 15, 235 â 245 ( 1996 ).; W. P. Kegelmeyer, J. M. Pruneda, P. D. Bourland, A. Hillis, M. W. Riggs, and M. L. Nipper, â Computerâ aided mammographic screening for spiculated lesions,â Radiology RADLAX --> 191, 331 â 337 ( 1994 ).; F. F. Yin, M. L. Giger, K. Doi, C. E. Metz, C. J. Vyborny, and R. A. Schmidt, â Computerized detection of masses in digital mammograms: Analysis of bilateral subtraction images. â Med. Phys. MPHYA6 --> 18, 955 â 963 ( 1991 ).; D. Brzakovic, X. M. Luo, and P. Brzakovic, â An approach to automated detection of tumors in mammograms,â IEEE Trans. Med. Imaging ITMID4 --> 9, 233 â 241 ( 1990 ).; H. D. Li, M. Kallergi, L. P. Clarke, V. K. Jain, and R. A. Clark, â Markov random field for tumor detection in digital ammography,â IEEE Trans. Med. Imaging ITMID4 --> 14, 565 â 576 ( 1995 ).; N. Petrick, H.â P. Chan, D. Wei, B. Sahiner, M. A. Helvie, and D. D. Adler, â Automated detection of breast masses on mammograms using adaptive contrast enhancement and texture classification,â Med. Phys. MPHYA6 --> 23, 1685 â 1696 ( 1996 ).; H. Kobatake, H. Ron Jin, Y. Yoshinaga, and S. Nawano, â Computer diagnosis of breast cancer by mammogram processing,â Radiologia Diagnostica 35, 29 â 33 ( 1994 ).; N. Petrick, H. P. Chan, B. Sahiner, and D. Wei, â An adaptive densityâ weighted contrast enhancement filter for mammographic breast mass detection,â IEEE Trans. Med. Imaging ITMID4 --> 15, 59 â 67 ( 1996 ).; B. Sahiner, H. P. Chan, N. Petrick, M. A. Helvie, and M. M. Goodsitt, â Computerized characterization of masses on mammograms: The rubber band straightening transform and texture analysis,â Med. Phys. MPHYA6 --> 25, 516 â 526 ( 1997 ).; N. Petrick, H. P. Chan, B. Sahiner, M. A. Helvie, M. M. Goodsitt, and D. D. Adler, â Computerâ aided breast mass detection: False positive reduction using breast tissue composition,â in Digital Mammography, edited by K. Doi, M. Giger, R. Nishikawa, and R. Schmidt (Elsevier, New York, 1996).; J. C. Russ, The Image Processing Handbook (CRC, Boca Rato, FL, 1992).; L. Xu, A. Krzyzak, and C. Y. Suen, â Methods of combining multiple classifiers and their applications to handwriting recognition,â IEEE Trans. Syst. Man Cybern. ISYMAW --> 22, 418 â 435 ( 1992 ).; J. Kilday, F. Palmieri, and M. D. Fox, â Classifying mammographic lesions using computerâ aided image analysis,â IEEE Trans. Med. Imaging ITMID4 --> 12, 664 â 669 ( 1993 ).; P. A. Lachenbruch, Discriminant Analysis (Hafner, New York, 1975).; R. O. Duda and P. E. Hart, Pattern Classification and Scene Analysis (Wiley, New York, 1973).; D. Wei, H. P. Chan, M. A. Helvie, B. Sahiner, N. Petrick, D. D. Adler, and M. M. Goodsitt, â Classification of mass and normal breast tissue on digital mammograms: Multiresolution texture analysis,â Med. Phys. MPHYA6 --> 22, 1501 â 1513 ( 1995 ).; D. Wei, H. P. Chan, N. Petrick, B. Sahiner, M. A. Helvie, D. D. Adler, and M. M. Goodsitt, â Falseâ positive reduction for detection of masses on digital mammograms: Global and local multiresolution texture analysis,â Med. Phys. MPHYA6 --> 24, 903 â 914 ( 1997 ).; R. M. Haralick, K. Shanmugam, and I. Dinstein, â Texture features for image classification,â IEEE Trans. Syst. Man Cybern. ISYMAW --> SMCâ 3, 610 â 621 ( 1973 ).; R. W. Conners, â Towards a set of statistical features which measure visually perceivable qualities of textures,â in Proceedings of the IEEE Conference on Pattern Recognition and Image Processing, pp. 382â 390 (1979).; D. Wei, H. P. Chan, M. A. Helvie, B. Sahiner, N. Petrick, D. D. Adler, and M. M. Goodsitt, â Multiresolution texture analysis for classification of mass and normal breast tissue on digital mammograms,â Proc. SPIE PSISDG --> 2434, 606 â 611 ( 1995 ).; H.â P. Chan, D. Wei, M. A. Helvie, B. Sahiner, D. D. Adler, M. M. Goodsitt, and N. Petrick, â Computerâ aided classification of mammographic masses and normal tissue: Linear discriminant analysis in texture feature space,â Phys. Med. Biol. PHMBA7 --> 40, 857 â 876 ( 1995 ).; D. P. Chakraborty, â Maximum likelihood analysis of freeâ response receiver operating characteristic (FROC) data,â Med. Phys. MPHYA6 --> 16, 561 â 568 ( 1989 ).; D. P. Chakraborty and L. H. L. Winter, â Freeâ response methodology, Alternate analysis and a new observerâ performance experiment,â Radiology RADLAX --> 174, 873 â 881 ( 1990 ).
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16Electronic Resource
المؤلفون: Petrick, N, Mori, K, Zhang, Jun, Cain, EH, Saha, A, Zhu, Z, Mazurowski, MA
مصطلحات الفهرس: Breast mass detection, fully convolutional network, Life Sciences & Biomedicine, mammography, Optics, Physical Sciences, Radiology, Nuclear Medicine & Medical Imaging, Science & Technology, tomosynthesis, transfer learning, Conference Paper
URL:
http://hdl.handle.net/10536/DRO/DU:30174884 https://dro.deakin.edu.au/eserv/DU:30174884/zhang-breastmassdetection-2018.pdf http://doi.org/10.1117/12.2295443 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000432546900074&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a045e4b2bb1f2b747c68c720ec8913b7 http://elements.deakin.edu.au/viewobject.html?id=351663&cid=1
issn: 1605-7422
issn: 1996-756X
isbn: 9781510616394
SPIE Medical imaginghttps://dro.deakin.edu.au/eserv/DU:30174884/zhang-breastmassdetection-2018.pdf http://doi.org/10.1117/12.2295443 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000432546900074&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a045e4b2bb1f2b747c68c720ec8913b7 http://elements.deakin.edu.au/viewobject.html?id=351663&cid=1
SPIE Medical Imaging 2018 : Computer-Aided Diagnosis : Proceedings of Society of Photo-Optical Instrumentation Engineers 2018 conference -
17Electronic Resource
المؤلفون: Egan, G, Salvado, O, Min, Hang, Chandra, Shekhar, Dhungel, Neeraj, Crozier, Stuart, Bradley, Andrew
المصدر: Proceedings of the 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)
مصطلحات الفهرس: Average sensitivities, Breast mass detection, Cascade of random forests, Class imbalance, Decision trees, False positive, Image segmentation, Mammography, Mass segmentation, Medical imaging, Morphological filtering, Segmentation, andom forests, Chapter in Book, Report or Conference volume
URL:
https://eprints.qut.edu.au/114136/2/114136.pdf https://eprints.qut.edu.au/114136/2/114136.pdf
doi:10.1109/ISBI.2017.7950481
Min, Hang, Chandra, Shekhar, Dhungel, Neeraj, Crozier, Stuart, & Bradley, Andrew (2017) Multi-scale mass segmentation for mammograms via cascaded random forests. In Egan, G & Salvado, O (Eds.) Proceedings of the 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017). Institute of Electrical and Electronics Engineers Inc., United States of America, pp. 113-117. -
18Electronic Resource
المؤلفون: Unal, G, Wells, W, Sabuncu, M R, Ourselin, S, Joskowicz, L, Dhungel, Neeraj, Carneiro, Gustavo, Bradley, Andrew
المصدر: Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016: 19th International Conference, Proceedings, Part II (Lecture Notes in Computer Science, Volume 9901)
مصطلحات الفهرس: Artificial intelligence, Breast mass, Breast mass classification, Breast mass detection, Classification (of information), Classification performance, Classification results, Deep learning, Learning systems, Machine learning models, Mammograms, Mammography, Medical imaging, Texture information, X ray screens, Chapter in Book, Report or Conference volume
URL: doi:10.1007/978-3-319-46723-8_13
Dhungel, Neeraj, Carneiro, Gustavo, & Bradley, Andrew (2016) The automated learning of deep features for breast mass classification from mammograms. In Unal, G, Wells, W, Sabuncu, M R, Ourselin, S, & Joskowicz, L (Eds.) Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016: 19th International Conference, Proceedings, Part II (Lecture Notes in Computer Science, Volume 9901). Springer, Switzerland, pp. 106-114.
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