Výsledky vyhledávání - "Idit Diamant"

Task-Driven Dictionary Learning Based on Mutual Information for Medical Image Classification

Autor: Eyal Klang, Idit Diamant, Eli Konen, Jacob Goldberger, Hayit Greenspan, Michal Amitai

Publikováno v: IEEE Transactions on Biomedical Engineering. 64:1380-1392

Objective: We present a novel variant of the bag-of-visual-words (BoVW) method for automated medical image classification. Methods: Our approach improves the BoVW model by learning a task-driven dictionary of the most relevant visual words per task u

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2b124359fffc75ce258737de9221cde8
https://doi.org/10.1109/tbme.2016.2605627

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Chest pathology identification using deep feature selection with non-medical training

Autor: Sivan Lieberman, Hayit Greenspan, Lior Wolf, Eli Konen, Yaniv Bar, Idit Diamant

Publikováno v: Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization. 6:259-263

We demonstrate the feasibility of detecting pathology in chest X-rays using deep learning approaches based on non-medical learning. Convolutional neural networks (CNN) learn higher level image representations. In this work, we explore the features ex

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::94a39a30deeb222c05dd831bdc408e4d
https://doi.org/10.1080/21681163.2016.1138324

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GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in Liver Lesion Classification

Autor: Maayan Frid-Adar, Michal Amitai, Jacob Goldberger, Hayit Greenspan, Idit Diamant, Eyal Klang

Deep learning methods, and in particular convolutional neural networks (CNNs), have led to an enormous breakthrough in a wide range of computer vision tasks, primarily by using large-scale annotated datasets. However, obtaining such datasets in the m

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f547405f28231b1397d913a4c25e2635
http://arxiv.org/abs/1803.01229

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CT Image-based Decision Support System for Categorization of Liver Metastases Into Primary Cancer Sites: Initial Results

Autor: Avi, Ben-Cohen, Eyal, Klang, Idit, Diamant, Noa, Rozendorn, Stephen P, Raskin, Eli, Konen, Michal Marianne, Amitai, Hayit, Greenspan

Publikováno v: Academic radiology. 24(12)

This study aimed to provide decision support for the human expert, to categorize liver metastases into their primary cancer sites. Currently, once a liver metastasis is detected, the process of finding the primary site is challenging, time-consuming,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::d5bf983f609226e35a8de7dce512982b
https://pubmed.ncbi.nlm.nih.gov/28778512

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Chest Radiograph Pathology Categorization via Transfer Learning

Autor: Ofer Geva, Sivan Lieberman, Eli Konen, Yaniv Bar, Hayit Greenspan, G. Zimmerman, Lior Wolf, Idit Diamant

Publikováno v: Deep Learning for Medical Image Analysis

The goal of this chapter is to give an overview of the research we have been conducting in automated X-ray pathology detection for the past 10 years, from bag-of-visual-words (BoVW) models to the Convolutional Neural Network (CNN) Deep Learning schem

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d1b04259de2eee08e569e4f6f1c83cdd
https://doi.org/10.1016/b978-0-12-810408-8.00018-3

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Contributors

Autor: R. Venkatesh Babu, Yaniv Bar, Joseph Blair, Andrew P. Bradley, Gustavo Carneiro, Hao Chen, Erik B. Dam, Idit Diamant, Qi Dou, Michael D. Feldman, Renee Frank, Yaozong Gao, Bogdan Georgescu, Ofer Geva, Florin C. Ghesu, Hayit Greenspan, Yanrong Guo, Pheng-Ann Heng, Joachim Hornegger, R. Todd Hurst, Christian Igel, Vamsi K. Ithapu, Andrew Janowczyk, Sterling C. Johnson, Michiel Kallenberg, Christopher B. Kendall, Minjeong Kim, Eli Konen, Srinivas S.S. Kruthiventi, Jianming Liang, Rui Liao, Sivan Lieberman, Le Lu, Anant Madabhushi, Kenneth B. Margulies, Dimitris Metaxas, Shun Miao, Vincent C.T. Mok, Konda R. Mopuri, Jacinto Nascimento, Hien Van Nguyen, Mads Nielsen, Jeffrey J. Nirschl, Akshay Pai, Eliot G. Peyster, Nikita Prabhu, Jing Qin, Ravi K. Sarvadevabhatla, Dinggang Shen, Lin Shi, Hoo-Chang Shin, Jae Y. Shin, Vikas Singh, Stefan Sommer, Suraj Srinivas, Heung-Il Suk, Ronald M. Summers, Nima Tajbakhsh, Yuan-Ching Teng, Raviteja Vemulapalli, Defeng Wang, Jane Z. Wang, Shaoyu Wang, Lior Wolf, Guorong Wu, Yuanpu Xie, Fuyong Xing, Zhennan Yan, Lin Yang, Lequan Yu, Yiqiang Zhan, Shaoting Zhang, Lei Zhao, S. Kevin Zhou, Xiang Sean Zhou, Gali Zimmerman

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::08515dc6c341cb0e65d35266883668cf
https://doi.org/10.1016/b978-0-12-810408-8.00029-8

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Modeling the Intra-class Variability for Liver Lesion Detection Using a Multi-class Patch-Based CNN

Autor: Michal Amitai, Jacob Goldberger, Maayan Frid-Adar, Idit Diamant, Eyal Klang, Hayit Greenspan

Publikováno v: Patch-Based Techniques in Medical Imaging ISBN: 9783319674339
Patch-MI@MICCAI

Automatic detection of liver lesions in CT images poses a great challenge for researchers. In this work we present a deep learning approach that models explicitly the variability within the non-lesion class, based on prior knowledge of the data, to s

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::51ce44574d3a731ad7138f5c77ed563b
https://doi.org/10.1007/978-3-319-67434-6_15

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Mutual information criterion for feature selection with application to classification of breast microcalcifications

Autor: Moran Shalhon, Hayit Greenspan, Jacob Goldberger, Idit Diamant

Publikováno v: Medical Imaging: Image Processing

Classification of clustered breast microcalcifications into benign and malignant categories is an extremely challenging task for computerized algorithms and expert radiologists alike. In this paper we present a novel method for feature selection base

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5ff0721cf58414f3bd04c72935f4c108
https://doi.org/10.1117/12.2216466

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Fully Convolutional Network for Liver Segmentation and Lesions Detection

Autor: Eyal Klang, Idit Diamant, Hayit Greenspan, Avi Ben-Cohen, M Amitai

Publikováno v: Deep Learning and Data Labeling for Medical Applications ISBN: 9783319469751
LABELS/DLMIA@MICCAI

In this work we explore a fully convolutional network (FCN) for the task of liver segmentation and liver metastases detection in computed tomography (CT) examinations. FCN has proven to be a very powerful tool for semantic segmentation. We explore th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::05f6a0739b161560779fddffef7bd018
https://doi.org/10.1007/978-3-319-46976-8_9

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Inhomogeneity of tissue-level strain distributions in individual trabeculae: Mathematical model studies of normal and osteoporosis cases

Autor: Idit Diamant, Sigal Portnoy, Amit Gefen

Publikováno v: Medical Engineering & Physics. 30:624-630

Little is known about the distributions of mechanical strains and stresses in individual trabeculae of cancellous bone, despite evidence that tissue-level strains affect the metabolism of bone. Recently, micro-finite element (micro-FE) studies have p

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::98da414ff7964bc02aba755a99cc24f9
https://doi.org/10.1016/j.medengphy.2007.07.001

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