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Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization Volume 6, 2018 - Issue 3: 1st MICCAI workshop on Deep Learning in Medical Image Analysis
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Original Articles

Computational mammography using deep neural networks

A. DubrovinaComputer Science, Technion, Haifa, Israel.Correspondence[email protected]
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P. KisilevIBM Haifa Research Lab, Haifa, Israel.View further author information
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B. GinsburgNVIDIA, Santa Clara, CA, USA.View further author information
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S. HashoulIBM Haifa Research Lab, Haifa, Israel.;Carmel Medical Center, Haifa, Israel.View further author information
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R. KimmelComputer Science, Technion, Haifa, Israel.View further author information
Pages 243-247 | Received 08 Nov 2015, Accepted 09 Dec 2015, Published online: 14 Mar 2016

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Amine Ben Slama, Hanene Sahli, Aymen Mouelhi, Jihene Marrakchi, Mounir Sayadi & Hedi Trabelsi. (2020) DBN-DNN: discrimination and classification of VNG sequence using deep neural network framework in the EMD domain. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization 8:6, pages 681-690.
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Lewlyn L. R. Rodrigues, Dasharathraj K Shetty, Nithesh Naik, Chetana Balakrishna Maddodi, Anuradha Rao, Ajith Kumar Shetty, Rama Bhat & B. M. Zeeshan Hameed. (2020) Machine learning in coronary heart disease prediction: Structural equation modelling approach. Cogent Engineering 7:1.
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Manimuthu Ayyannan, Mohanarathinam A, Sathya D, Nithya T, Tamilnidhi M & Neelam Sanjeev Kumar. (2023) Medical Image Classification using Deep Learning Techniques: A Review. Medical Image Classification using Deep Learning Techniques: A Review.
Santiago V. Silva, Cesar A. Sierra-Franco, Jan Hurtado, Leonardo C. da Cruz, Victor de A. Thomaz, Greis Francy M. Silva-Calpa & Alberto B. Raposo. 2023. Advances in Visual Computing. Advances in Visual Computing 56 67 .
Veli-Matti Sundell, Teemu Mäkelä, Anne-Mari Vitikainen & Touko Kaasalainen. (2022) Convolutional neural network -based phantom image scoring for mammography quality control. BMC Medical Imaging 22:1.
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V.M. Tiryaki & V. Kaplanoğlu. (2022) Deep Learning-Based Multi-Label Tissue Segmentation and Density Assessment from Mammograms. IRBM 43:6, pages 538-548.
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Mohamed A. Abdou. (2022) Literature review: efficient deep neural networks techniques for medical image analysis. Neural Computing and Applications 34:8, pages 5791-5812.
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Kuochen Zhou, Wei Li & Dazhe Zhao. (2022) Deep learning-based breast region extraction of mammographic images combining pre-processing methods and semantic segmentation supported by Deeplab v3+. Technology and Health Care, pages 1-18.
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Yoshio Rubio & Oscar Montiel. (2021) Multicriteria Evaluation of Deep Neural Networks for Semantic Segmentation of Mammographies. Axioms 10:3, pages 180.
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Abhijith Reddy Beeravolu, Sami Azam, Mirjam Jonkman, Bharanidharan Shanmugam, Krishnan Kannoorpatti & Adnan Anwar. (2021) Preprocessing of Breast Cancer Images to Create Datasets for Deep-CNN. IEEE Access 9, pages 33438-33463.
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Mario Mustra & Andrija Stajduhar. (2020) Segmentation Masks for the Mini-Mammographic Image Analysis Society (mini-MIAS) Database. IEEE Consumer Electronics Magazine 9:5, pages 28-33.
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Vaira Suganthi Gnanasekaran, Sutha Joypaul & Parvathy Meenakshi Sundaram. (2020) A Survey on Machine Learning Algorithms for the Diagnosis of Breast Masses with Mammograms. Current Medical Imaging Formerly Current Medical Imaging Reviews 16:6, pages 639-652.
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Nassima Dif & Zakaria Elberrichi. (2020) A New Deep Learning Model Selection Method for Colorectal Cancer Classification. International Journal of Swarm Intelligence Research 11:3, pages 72-88.
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Gerson Africano, Otso Arponen, Antti Sassi, Irina Rinta-Kiikka, Anna-Leena Laaperi & Said Pertuz. (2020) A New Benchmark and Method for the Evaluation of Chest Wall Detection in Digital Mammography * . A New Benchmark and Method for the Evaluation of Chest Wall Detection in Digital Mammography * .
Hossein Soleimani & Oleg V. Michailovich. (2020) On Segmentation of Pectoral Muscle in Digital Mammograms by Means of Deep Learning. IEEE Access 8, pages 204173-204182.
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S. Velliangiri, P. Karthikeyan, Iwin Thanakumar Joseph & Satish A. P. Kumar. (2019) Investigation of Deep Learning Schemes in Medical Application. Investigation of Deep Learning Schemes in Medical Application.
Ygor Reboucas Serpa, Leonardo Augusto Pires & Maria Andreia Formico Rodrigues. (2019) Milestones and New Frontiers in Deep Learning. Milestones and New Frontiers in Deep Learning.
Dina Abdelhafiz, Clifford Yang, Reda Ammar & Sheida Nabavi. (2019) Deep convolutional neural networks for mammography: advances, challenges and applications. BMC Bioinformatics 20:S11.
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Yujie Li, Shuxue Ding, Xiang Li, Benying Tan & Atsunori Kanemura. (2019) Residual-Network-Based Supervised Gaze Prediction for First-Person Videos. IEEE Access 7, pages 56208-56216.
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Mihalj Bakator & Dragica Radosav. (2018) Deep Learning and Medical Diagnosis: A Review of Literature. Multimodal Technologies and Interaction 2:3, pages 47.
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Emmanuel Maggiori, Yuliya Tarabalka, Guillaume Charpiat & Pierre Alliez. (2017) High-Resolution Aerial Image Labeling With Convolutional Neural Networks. IEEE Transactions on Geoscience and Remote Sensing 55:12, pages 7092-7103.
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Gustavo Carneiro, Jacinto Nascimento & Andrew P. Bradley. (2017) Automated Analysis of Unregistered Multi-View Mammograms With Deep Learning. IEEE Transactions on Medical Imaging 36:11, pages 2355-2365.
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Gustavo Carneiro, Yefeng Zheng, Fuyong Xing & Lin Yang. 2017. Deep Learning and Convolutional Neural Networks for Medical Image Computing. Deep Learning and Convolutional Neural Networks for Medical Image Computing 11 32 .
Jorge Hernández Rodríguez, Francisco Javier Cabrero Fraile, María José Rodríguez Conde & Pablo Luis Gómez Llorente. (2016) Computer aided detection and diagnosis in medical imaging. Computer aided detection and diagnosis in medical imaging.

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