Computer-aided diagnosis in medical imaging: Historical review, current status and future potential

Cited by (1,000)

Items 101–200 of 1,000

1. Probabilistic neural network for breast cancer classification
   Ahmad Taher Azar, Shaimaa Ahmed Elsaid · 2012 · Neural Computing and Applications
2. A Comprehensive Survey on the Detection, Classification, and Challenges of Neurological Disorders
   Aklima Akter Lima, M. F. Mridha, Sujoy Chandra Das, Md. Mohsin Kabir, Md. Rashedul Islam, Yutaka Watanobe · 2022 · Biology
3. Computer-aided diagnosis of lung nodule using gradient tree boosting and Bayesian optimization
   Mizuho Nishio, Mitsuo Nishizawa, Osamu Sugiyama, Ryosuke Kojima, Masahiro Yakami, Tomohiro Kuroda, Kaori Togashi · 2018 · PLoS ONE
4. Semi-automated detection of anterior cruciate ligament injury from MRI
   Ivan Štajduhar, Mihaela Mamula, Damir Miletić, Gözde Ünal · 2016 · Computer Methods and Programs in Biomedicine
5. ADD-Net: An Effective Deep Learning Model for Early Detection of Alzheimer Disease in MRI Scans
   Mian Muhammad Sadiq Fareed, Shahid Zikria, Gulnaz Ahmed, Mui-zzud-din, Saqib Mahmood, Muhammad Aslam, Syeda Fizzah Jilani, Ahmad Moustafa, Muhammad Asad · 2022 · IEEE Access
6. Deep learning analysis for the detection of pancreatic cancer on endosonographic images: a pilot study
   Tonozuka, Ryosuke, Itoi, Takao, Nagata, Naoyoshi, Kojima, Hiroyuki, Sofuni, Atsushi, Tsuchiya, Takayoshi, Ishii, Kentaro, Tanaka, Reina, Nagakawa, Yuichi, Mukai, Shuntaro · 2021 · Journal of Hepato-Biliary-Pancreatic Sciences
7. Sketch guided and progressive growing GAN for realistic and editable ultrasound image synthesis
   Jiamin Liang, Xin Yang, Yuhao Huang, Haoming Li, Shuangchi He, Xindi C. Hu, Zejian Chen, Wufeng Xue, Jun Cheng, Dong Ni · 2022 · Medical Image Analysis
8. A two‐stream deep neural network‐based intelligent system for complex skin cancer types classification
   Muhammad Attique Khan, Muhammad Yusof Sharif, Tallha Akram, Seifedine Kadry, Ching‐Hsien Hsu · 2021 · International Journal of Intelligent Systems
9. PCA-PNN and PCA-SVM Based CAD Systems for Breast Density Classification
   N.A. Kriti, Jitendra Virmani, Nilanjan Dey, Vinod Kumar · 2015 · Intelligent systems reference library
10. Diagnosing Expertise: Human Capital, Decision Making, and Performance among Physicians
    Janet Currie, William Bentley MacLeod · 2016 · Journal of Labor Economics
11. Machine learning-based diagnosis of breast cancer utilizing feature optimization technique
    Khandaker Mohammad Mohi Uddin, Nitish Biswas, Sarreha Tasmin Rikta, Samrat Kumar Dey · 2023 · Computer Methods and Programs in Biomedicine Update
12. A Transfer Learning Method for Pneumonia Classification and Visualization
    Juan Eduardo Luján-García, Cornelio Yáñez-Márquéz, Yenny Villuendas-Rey, Oscar Camacho-Nieto · 2020 · Applied Sciences
13. Role of Gist and PHOG Features in Computer-Aided Diagnosis of Tuberculosis without Segmentation
    Arun Chauhan, Devesh Chauhan, Chittaranjan Rout · 2014 · PLoS ONE
14. Prognostic Value of the Quantitative Metabolic Volumetric Measurement on 18F-FDG PET/CT in Stage IV Nonsurgical Small-cell Lung Cancer
    Shengri Liao, Bill C. Penney, Hao Zhang, Kenji Suzuki, Yonglin Pu · 2011 · Academic Radiology
15. Computer-Assisted Interpretation of Planar Whole-Body Bone Scans
    May Sadik, Iman Hamadeh, Pierre Nordblom, Madis Suurküla, Peter Höglund, Mattias Ohlsson, Lars Edenbrandt · 2008 · Journal of Nuclear Medicine
16. Artificial intelligence in radiology
    Luka Filipović-Grčić, Filip Đerke · 2019 · Rad Hrvatske akademije znanosti i umjetnosti Medicinske znanosti
17. Deep‐Learning Detection of Cancer Metastases to the Brain on MRI
    Min Zhang, Geoffrey S. Young, Huai Chen, Jing Li, Lei Qin, Jose Ricardo McFaline-Figueroa, David A. Reardon, Xinhua Cao, Xian Wu, Xiaoyin Xu · 2020 · Journal of Magnetic Resonance Imaging
18. CGMVQA: A New Classification and Generative Model for Medical Visual Question Answering
    Fuji Ren, Yangyang Zhou · 2020 · IEEE Access
19. Computer-aided diagnosis: The emerging of three CAD systems induced by Japanese health care needs
    Hiroshi Fujita, Yoshikazu Uchiyama, Toshiaki Nakagawa, Daisuke Fukuoka, Yuji Hatanaka, Takeshi Hara, Gobert N. Lee, Yoshinori Hayashi, Yuji Ikedo, Xin Gao et al. · 2008 · Computer Methods and Programs in Biomedicine
20. Differentiation of Pancreatic Cancer and Chronic Pancreatitis Using Computer-Aided Diagnosis of Endoscopic Ultrasound (EUS) Images: A Diagnostic Test
    Zhu, Maoling, Xu, Can, Yu, Jianguo, Wu, Yijun, Li, Chunguang, Zhang, Minmin, Jin, Zhendong, Li, Zhaoshen · 2013 · PLoS ONE
21. Automated characterization of fatty liver disease and cirrhosis using curvelet transform and entropy features extracted from ultrasound images
    U. Rajendra Acharya, U. Raghavendra, Hamido Fujita, Yuki Hagiwara, Joel EW Koh, Tan Jen Hong, Vidya K. Sudarshan, Anushya Vijayananthan, Chai Hong Yeong, Anjan Gudigar et al. · 2016 · Computers in Biology and Medicine
22. Deep Learning Algorithms with Demographic Information Help to Detect Tuberculosis in Chest Radiographs in Annual Workers’ Health Examination Data
    Seok‐Jae Heo, Yangwook Kim, Sehyun Yun, Sung‐Shil Lim, Jihyun Kim, Chung Mo Nam, Eun‐Cheol Park, Inkyung Jung, Jin‐Ha Yoon · 2019 · International Journal of Environmental Research and Public Health
23. Boosted EfficientNet: Detection of Lymph Node Metastases in Breast Cancer Using Convolutional Neural Networks
    Jun Wang, Qianying Liu, Haotian Xie, Zhaogang Yang, Hefeng Zhou · 2021 · Cancers
24. Uncertainty-guided dual-views for semi-supervised volumetric medical image segmentation
    Himashi Peiris, Munawar Hayat, Zhaolin Chen, Gary F. Egan, Mehrtash Tafazzoli Harandi · 2023 · Nature Machine Intelligence
25. A hybrid Fuzzy C-Means and Neutrosophic for jaw lesions segmentation
    Mutasem K. Alsmadi · 2016 · Ain Shams Engineering Journal
26. Risk-Aware Machine Learning Classifier for Skin Lesion Diagnosis
    Aryan Mobiny, Aditi Singh, Hien Van Nguyen · 2019 · Journal of Clinical Medicine
27. Artificial Intelligence for the Future Radiology Diagnostic Service
    Seong K. Mun, Kenneth H. Wong, Shih‐Chung B. Lo, Yanni Li, Shijir Bayarsaikhan · 2021 · Frontiers in Molecular Biosciences
28. Parallel implementation for 3D medical volume fuzzy segmentation
    Shadi Mahmoud Faleh AlZu’bi, Mohammed A. Shehab, Mahmoud Al‐Ayyoub, Yaser Jararweh, Brij Bhooshan Gupta · 2018 · Pattern Recognition Letters
29. Texture Analysis and Its Applications in Biomedical Imaging: A Survey
    Maryam Khaksar Ghalati, Ana Nunes, Hugo R. L. Ferreira, Pedro Serranho, Rui Bernardes · 2021 · IEEE Reviews in Biomedical Engineering
30. Evolution of Surgical Robot Systems Enhanced by Artificial Intelligence: A Review
    Yanzhen Liu, Xinbao Wu, Yudi Sang, Chunpeng Zhao, Yu Wang, Bojing Shi, Yubo Fan · 2024 · Advanced Intelligent Systems
31. Computer‐aided detection of metastatic brain tumors using automated three‐dimensional template matching
    Robert Ambrosini, Peng Wang, Walter G. O’Dell · 2009 · Journal of Magnetic Resonance Imaging
32. Optimizing Analysis, Visualization, and Navigation of Large Image Data Sets: One 5000-Section CT Scan Can Ruin Your Whole Day
    Katherine P. Andriole, Jeremy M. Wolfe, Ramin Khorasani, S. Ted Treves, David J. Getty, Francine L. Jacobson, Michael L. Steigner, John J. Pan, Arkadiusz Sitek, Steven E. Seltzer · 2011 · Radiology
33. Effect of a Deep Learning Framework-Based Computer-Aided Diagnosis System on the Diagnostic Performance of Radiologists in Differentiating between Malignant and Benign Masses on Breast Ultrasonography
    Choi, Ji Soo, Han, Boo-Kyung, Ko, Eun Sook, Bae, Jung Min, Ko, Eun Young, Song, So Hee, Kwon, Mi-ri, Shin, Jung Hee, Hahn, Soo Yeon · 2019 · Korean Journal of Radiology
34. Artificial Intelligence in Breast Imaging: Potentials and Limitations
    Ellen B. Mendelson · 2018 · American Journal of Roentgenology
35. Vision Transformer for femur fracture classification
    Leonardo Tanzi, Andrea Audisio, Giansalvo Cirrincione, Alessandro Aprato, Enrico Vezzetti · 2022 · Injury
36. Automatic captioning for medical imaging (MIC): a rapid review of literature
    Djamila Romaissa Beddiar, Mourad Oussalah, Tapio Seppänen · 2022 · Artificial Intelligence Review
37. Developing, purchasing, implementing and monitoring AI tools in radiology: practical considerations. A multi-society statement from the ACR, CAR, ESR, RANZCR & RSNA
    Adrian P. Brady, Bibb Allen, Jaron Chong, Elmar Kotter, Nina E. Kottler, John Mongan, Lauren Oakden‐Rayner, Daniel Pinto dos Santos, An Tang, Christoph Wald et al. · 2024 · Insights into Imaging
38. Prospects of Structural Similarity Index for Medical Image Analysis
    Mudeng, Vicky, Kim, Minseok, Choe, Se-woon · 2022 · Applied Sciences
39. Three-Dimensional CT Image Segmentation by Combining 2D Fully Convolutional Network with 3D Majority Voting
    Xiangrong Zhou, Takaaki Ito, Ryosuke Takayama, Song Wang, Takeshi Hara, Hiroshi Fujita · 2016 · Lecture notes in computer science
40. Role of Big Data and Machine Learning in Diagnostic Decision Support in Radiology
    Tanveer Fathima Syeda-Mahmood · 2018 · Journal of the American College of Radiology
41. Artificial Intelligence: reshaping the practice of radiological sciences in the 21st century
    Issam El Naqa, Masoom A. Haider, Maryellen Lissak Giger, Randall K. Ten Haken · 2020 · British Journal of Radiology
42. Computer aided detection of ureteral stones in thin slice computed tomography volumes using Convolutional Neural Networks
    Martin Längkvist, Johan Jendeberg, Per Thunberg, Amy Loutfi, Mats Lidén · 2018 · Computers in Biology and Medicine
43. Application of artificial intelligence in ophthalmology
    Xueli Du, Wenbo Li, Bojie Hu · 2018 · International Journal of Ophthalmology
44. A Comprehensive Survey on Deep-Learning-Based Breast Cancer Diagnosis
    M. F. Mridha, Md. Abdul Hamid, Muhammad Mostafa Monowar, Ashfia Jannat Keya, Abu Quwsar Ohi, Md. Rashedul Islam, Jong-Myon Kim · 2021 · Cancers
45. Discriminating solitary cysts from soft tissue lesions in mammography using a pretrained deep convolutional neural network
    Thijs Kooi, Bram van Ginneken, Nico Karssemeijer, Ard den Heeten · 2017 · Medical Physics
46. A survey on cancer detection via convolutional neural networks: Current challenges and future directions
    Pallabi Sharma, Deepak Ranjan Nayak, Bunil Kumar Balabantaray, M. Tanveer, Rajashree Nayak · 2023 · Neural Networks
47. Segmentation of Lungs in Chest X-Ray Image Using Generative Adversarial Networks
    Faizan Munawar, Shoaib Azmat, Talha Iqbal, Christer Grönlund, Hazrat Ali · 2020 · IEEE Access
48. Transformers Improve Breast Cancer Diagnosis from Unregistered Multi-View Mammograms
    Xuxin Chen, Ke Zhang, Ximin Wang, Neman Abdoli, Patrik Gilley, Hong Liu, Bin Zheng, Yuchen Qiu · 2022 · Diagnostics
49. Deep Learning in Cervical Cancer Diagnosis: Architecture, Opportunities, and Open Research Challenges
    Nina Youneszade, Mohsen Marjani, Pei Pei Chong · 2023 · IEEE Access
50. Advances of AI in image-based computer-aided diagnosis: A review
    Mst. Nilufa Yeasmin, Md Al Amin, Tasmim Jamal Joti, Zeyar Aung, Mohammad Abdul Azim · 2024 · Array
51. A Hybrid Knowledge-Guided Detection Technique for Screening of Infectious Pulmonary Tuberculosis From Chest Radiographs
    Rui Shen, Irene Cheng, Anup Basu · 2010 · IEEE Transactions on Biomedical Engineering
52. Trends in Deep Learning for Medical Hyperspectral Image Analysis
    Uzair Khan, Sidike Paheding, Colin P. Elkin, Vijaya Kumar Devabhaktuni · 2021 · IEEE Access
53. Pixel-Based Machine Learning in Medical Imaging
    Kenji Suzuki · 2012 · International Journal of Biomedical Imaging
54. Computer-aided diagnosis in chest radiography: Beyond nodules
    Bram van Ginneken, Laurens Hogeweg, Mathias Prokop · 2009 · European Journal of Radiology
55. Application of wavelet techniques for cancer diagnosis using ultrasound images: A Review
    Vidya K. Sudarshan, Muthu Rama Krishnan Mookiah, U. Rajendra Acharya, Vinod Chandran, Filippo Molinari, Hamido Fujita, Kwan Hoong Ng · 2015 · Computers in Biology and Medicine
56. Visual Computing for Medicine: Theory, Algorithms, and Applications
    Bernhard Preim, Charl P. Botha · 2007
57. Medical image classification using spatial adjacent histogram based on adaptive local binary patterns
    Dong Liu, Shengsheng Wang, Dezhi Huang, Gang Deng, Fantao Zeng, Huiling Chen · 2016 · Computers in Biology and Medicine
58. Vision–Language Model for Visual Question Answering in Medical Imagery
    Yakoub Bazi, Mohamad Mahmoud Al Rahhal, Laila Bashmal, Mansour Zuair · 2023 · Bioengineering
59. Artificial intelligence-assisted dermatology diagnosis: From unimodal to multimodal
    Nan Luo, Xiaojing Zhong, Luxin Su, Zilin Cheng, Wenyi Ma, Pingsheng Hao · 2023 · Computers in Biology and Medicine
60. Computer-aided diagnosis: A survey with bibliometric analysis
    Ryohei Takahashi, Yuya Kajikawa · 2017 · International Journal of Medical Informatics
61. Retrieval From and Understanding of Large-Scale Multi-modal Medical Datasets: A Review
    Henning Müller, Devrim Ünay · 2017 · IEEE Transactions on Multimedia
62. Integrated imaging and molecular analysis to decipher tumor microenvironment in the era of immunotherapy
    Jia Wu, Aaron T. Mayer, Ruijiang Li · 2020 · Seminars in Cancer Biology
63. Automated detection of lung nodules in computed tomography images: a review
    S. L. A. Lee, Abbas Z. Kouzani, Eric Jing Hu · 2010 · Machine Vision and Applications
64. Computer-Aided Detection of Architectural Distortion in Prior Mammograms of Interval Cancer
    Rangaraj Mandayam Rangayyan, Shantanu Banik, J. E. Leo Desautels · 2010 · Journal of Imaging Informatics in Medicine
65. Global localization of 3D anatomical structures by pre-filtered Hough Forests and discrete optimization
    René Donner, Bjoern H. Menze, Horst Bischof, Georg Langs · 2013 · Medical Image Analysis
66. Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges
    Fabian Isensee, Paul F. Jaeger, Peter M. Full, Ivo Wolf A, Sandy Engelhardt, Klaus H. Maier-Hein · 2018 · Lecture notes in computer science
67. Variation in algorithm implementation across radiomics software
    Joseph J. Foy, Kayla Robinson, Hui Li, Maryellen Lissak Giger, Hania Al‐Hallaq, Samuel G. Armato · 2018 · Journal of medical imaging
68. Breast Cancer Image Classification via Multi-Network Features and Dual-Network Orthogonal Low-Rank Learning
    Yongjun Wang, Baiying Lei, Ahmed Elazab, Ee-Leng Tan, Wei Wang, Fanglin Huang, Xuehao Gong, Tianfu Wang · 2020 · IEEE Access
69. Computer-aided diagnosis system for tissue characterization of brain tumor on magnetic resonance images
    Megha P. Arakeri, G. Ram Mohana Reddy · 2013 · Signal Image and Video Processing
70. Integrating geometric configuration and appearance information into a unified framework for anatomical landmark localization
    Martin Urschler, Thomas Ebner, Darko Štern · 2017 · Medical Image Analysis
71. A review of computer-aided diagnosis in thoracic and colonic imaging.
    Kenji Suzuki · 2012 · PubMed Central
72. AI and machine learning ethics, law, diversity, and global impact
    Drabiak, Katherine, Kyzer, Skylar, Nemov, Valerie, El Naqa, Issam · 2023 · The British Journal of Radiology
73. Brain Hemorrhage Diagnosis by Using Deep Learning
    Tong Duc Phong, Hieu Ngoc Duong, Hien Phuong Nhat Nguyen, Nguyen Thanh Trong, Vu Nguyen, Tran Van Hoa, Václav Snåšel · 2017 · International Conference on Machine Learning and Soft Computing (ICMLSC)
74. Breast and Colon Cancer Classification from Gene Expression Profiles Using Data Mining Techniques
    Mohamed Loey, Mohammed Wajeeh Jasim, Hazem Mokhtar El-Bakry, Mohamed Hamed N. Taha, Nour Eldeen M. Khalifa · 2020 · Symmetry
75. Improved Classifications of Planar Whole-Body Bone Scans Using a Computer-Assisted Diagnosis System: A Multicenter, Multiple-Reader, Multiple-Case Study
    May Sadik, Madis Suurküla, Peter Höglund, Andreas Järund, Lars Edenbrandt · 2009 · Journal of Nuclear Medicine
76. A review of computer aided detection in mammography
    Janine T Katzen, Katerina Dodelzon · 2018 · Clinical Imaging
77. Artificial intelligence in multiparametric prostate cancer imaging with focus on deep-learning methods
    Rogier R. Wildeboer, Ruud J. G. van Sloun, Hessel Wijkstra, Massimo Mischi · 2020 · Computer Methods and Programs in Biomedicine
78. Computer-assisted detection of infectious lung diseases: A review
    Ulaş Bağcı, Mike Bray, Jesus J. Caban, Jianhua Yao, Daniel J. Mollura · 2011 · Computerized Medical Imaging and Graphics
79. Dual-Path Adversarial Learning for Fully Convolutional Network (FCN)-Based Medical Image Segmentation
    Lei Bi, Dagan D. Feng, Jinman Kim · 2018 · The Visual Computer
80. Lung-RADS Version 1.1: Challenges and a Look Ahead, From the AJR Special Series on Radiology Reporting and Data Systems
    Lydia Chelala, Rydhwana Hossain, Ella Annabelle Kazerooni, Jared D. Christensen, Debra Sue Dyer, CHARLES STANLEY WHITE · 2021 · American Journal of Roentgenology
81. Automated detection of multiple sclerosis lesions in serial brain MRI
    Xavier Lladó, Onur Ganiler, Arnau Oliver, Robert Martí, Jordi Freixenet, Laia Valls, Joan Carles Vilanova, Lluís Ramió‐Torrentà, Àlex Rovira · 2011 · Neuroradiology
82. Automatic Lung Segmentation Using Control Feedback System: Morphology and Texture Paradigm
    Norliza Mohd Noor, Joel Chia Ming Than, Omar Mohd Rijal, Rosminah M. Kassim, Ashari Yunus, Amir A. Zeki, Michele Anzidei, Luca Saba, Jasjit S. Suri · 2015 · Journal of Medical Systems
83. Medical Image Synthesis with Generative Adversarial Networks for Tissue Recognition
    Qianqian Zhang, Haifeng Wang, Hongya Lu, Daehan Won, Sang Won Yoon · 2018 · IEEE International Conference on Healthcare Informatics (ICHI)
84. Automated detection and labelling of teeth and small edentulous regions on cone-beam computed tomography using convolutional neural networks
    Maurício do Nascimento Gerhardt, Rocharles Cavalcante Fontenele, André Ferreira Leite, Pierre Lahoud, Adriaan Van Gerven, Holger Willems, Andreas Smolders, Thomas Beznik, Reinhilde Jacobs · 2022 · Journal of Dentistry
85. A Survey of Convolutional Neural Network in Breast Cancer
    Ziquan Zhu, Shuihua Wang, Yudong Zhang · 2022 · Computer Modeling in Engineering & Sciences
86. Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement from the ACR, CAR, ESR, RANZCR and RSNA
    Adrian P. Brady, Bibb Allen, Jaron Chong, Elmar Kotter, Nina E. Kottler, John Mongan, Lauren Oakden‐Rayner, Daniel Pinto dos Santos, An Tang, Christoph Wald et al. · 2024 · Radiology Artificial Intelligence
87. Detection of Architectural Distortion in Prior Mammograms
    Sharmili Banik, Rangaraj Mandayam Rangayyan, J. E. Leo Desautels · 2010 · IEEE Transactions on Medical Imaging
88. Magnetic Resonance Imaging-Based Radiomic Profiles Predict Patient Prognosis in Newly Diagnosed Glioblastoma Before Therapy
    Sean D. McGarry, Sarah L. Hurrell, Amy L. Kaczmarowski, Elizabeth J. Cochran, Jennifer Connelly, Scott D. Rand, Kathleen M. Schmainda, Peter S. LaViolette · 2016 · Tomography
89. Effective Pneumothorax Detection for Chest X-Ray Images Using Local Binary Pattern and Support Vector Machine
    Yuan-Hao Chan, Yong-Zhi Zeng, Hsien-Chu Wu, Ming-Chi Wu, Hung–Min Sun · 2018 · Journal of Healthcare Engineering
90. Reproducible Machine Learning Methods for Lung Cancer Detection Using Computed Tomography Images: Algorithm Development and Validation
    Kun‐Hsing Yu, Michael T. Lee, Ming-Hsuan Yen, Samuel C. Kou, Bruce Robert Rosen, Jung-Hsien Chiang, Isaac S. Kohane · 2020 · Journal of Medical Internet Research
91. Deep Learning–Based Brain Computed Tomography Image Classification with Hyperparameter Optimization through Transfer Learning for Stroke
    Yung-Ting Chen, Yao-Liang Chen, Yi-Yun Chen, Yu‐Ting Huang, Ho-Fai Wong, Jiun‐Lin Yan, Jiun‐Jie Wang · 2022 · Diagnostics
92. LCD-Capsule Network for the Detection and Classification of Lung Cancer on Computed Tomography Images
    A. R. Bushara, R. S. Vinod Kumar, S. S. Kumar · 2023 · Multimedia Tools and Applications
93. Prognostic prediction of hypertensive intracerebral hemorrhage using CT radiomics and machine learning
    Xinghua Xu, Jiashu Zhang, Kai Ge Yang, Qun Wang, Xiaolei Chen, Bainan Xu · 2021 · Brain and Behavior
94. Convolution neural networks for optical coherence tomography (OCT) image classification
    K. Karthik, Manjunatha Mahadevappa · 2022 · Biomedical Signal Processing and Control
95. Prospects of deep learning for medical imaging
    Jonghoon Kim, Jisu Hong, Hyunjin Park · 2018 · Precision and Future Medicine
96. Accelerating 3D medical volume segmentation using GPUs
    Mahmoud Al‐Ayyoub, Shadi Mahmoud Faleh AlZu’bi, Yaser Jararweh, Mohammed A. Shehab, Brij Bhooshan Gupta · 2016 · Multimedia Tools and Applications
97. Classification of Breast Masses Using Selected Shape, Edge-sharpness, and Texture Features with Linear and Kernel-based Classifiers
    Tingting Mu, Asoke Kumar Nandi, Rangaraj Mandayam Rangayyan · 2008 · Journal of Imaging Informatics in Medicine
98. Machine learning methods for the classification of gliomas: Initial results using features extracted from MR spectroscopy
    G. Ranjith, R Parvathy, Vikas V. Vazhayil, Chandrasekharan Kesavadas, Suresh Nair · 2015 · The Neuroradiology Journal
99. A review of breast boundary and pectoral muscle segmentation methods in computer-aided detection/diagnosis of breast mammography
    Mehrdad Moghbel, Chia Yee Ooi, Nordinah Binti Ismail, Yuan Wen Hau, Nogol Memari · 2019 · Artificial Intelligence Review
100. Development and assessment of an individualized nomogram to predict colorectal cancer liver metastases
     Mingyang Li, Xueyan Li, Guo Yu, Zheng Miao, Xiaoming Liu, Shuxu Guo, Huimao Zhang · 2020 · Quantitative Imaging in Medicine and Surgery