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2020 – today
- 2023
[i7]Roi Peleg, Roi Weiss, Assaf Hoogi:
Leveraging the Triple Exponential Moving Average for Fast-Adaptive Moment Estimation. CoRR abs/2306.01423 (2023)- [i6]Ella Eidlin, Assaf Hoogi, Nathan S. Netanyahu:
Unsupervised Iterative U-Net with an Internal Guidance Layer for Vertebrae Contrast Enhancement in Chest X-Ray Images. CoRR abs/2306.03983 (2023) - 2022
- [j7]Guy Gaziv
, Roman Beliy, Niv Granot, Assaf Hoogi, Francesca Strappini, Tal Golan, Michal Irani:
Self-supervised Natural Image Reconstruction and Large-scale Semantic Classification from Brain Activity. NeuroImage 254: 119121 (2022) - [c5]Assaf Hoogi, Brian Wilcox, Yachee Gupta, Daniel L. Rubin:
Self-attention Capsule Network for Tissue Classification in Case of Challenging Medical Image Statistics. ECCV Workshops (3) 2022: 219-235 - 2020
- [j6]Assaf Hoogi, Arjun Mishra, Francisco Gimenez, Jeffrey Dong, Daniel L. Rubin:
Natural Language Generation Model for Mammography Reports Simulation. IEEE J. Biomed. Health Informatics 24(9): 2711-2717 (2020)
2010 – 2019
- 2019
- [c4]Ali Hatamizadeh, Assaf Hoogi, Debleena Sengupta, Wuyue Lu, Brian Wilcox, Daniel L. Rubin, Demetri Terzopoulos:
Deep Active Lesion Segmentation. MLMI@MICCAI 2019: 98-105 - [c3]Roman Beliy, Guy Gaziv, Assaf Hoogi, Francesca Strappini, Tal Golan, Michal Irani:
From voxels to pixels and back: Self-supervision in natural-image reconstruction from fMRI. NeurIPS 2019: 6514-6524 - [i5]Assaf Hoogi, Brian Wilcox, Yachee Gupta, Daniel L. Rubin:
Self-Attention Capsule Networks for Image Classification. CoRR abs/1904.12483 (2019) - [i4]Roman Beliy, Guy Gaziv, Assaf Hoogi, Francesca Strappini, Tal Golan, Michal Irani:
From voxels to pixels and back: Self-supervision in natural-image reconstruction from fMRI. CoRR abs/1907.02431 (2019) - [i3]Ali Hatamizadeh, Assaf Hoogi, Debleena Sengupta, Wuyue Lu, Brian Wilcox, Daniel L. Rubin, Demetri Terzopoulos:
Deep Active Lesion Segmentation. CoRR abs/1908.06933 (2019) - 2017
- [j5]Zeynettin Akkus, Alfiia Galimzianova, Assaf Hoogi, Daniel L. Rubin, Bradley J. Erickson:
Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions. J. Digit. Imaging 30(4): 449-459 (2017) - [j4]Assaf Hoogi, Christopher F. Beaulieu, Guilherme M. Cunha, Elhamy Heba, Claude B. Sirlin, Sandy Napel, Daniel L. Rubin:
Adaptive local window for level set segmentation of CT and MRI liver lesions. Medical Image Anal. 37: 46-55 (2017) - [j3]Assaf Hoogi, Arjun Subramaniam, Rishi Veerapaneni, Daniel L. Rubin:
Adaptive Estimation of Active Contour Parameters Using Convolutional Neural Networks and Texture Analysis. IEEE Trans. Medical Imaging 36(3): 781-791 (2017) - [i2]Assaf Hoogi, John W. Lambert, Yefeng Zheng, Dorin Comaniciu, Daniel L. Rubin:
A Fully-Automated Pipeline for Detection and Segmentation of Liver Lesions and Pathological Lymph Nodes. CoRR abs/1703.06418 (2017) - 2016
- [j2]Jocelyn Barker, Assaf Hoogi, Adrien Depeursinge, Daniel L. Rubin:
Automated classification of brain tumor type in whole-slide digital pathology images using local representative tiles. Medical Image Anal. 30: 60-71 (2016) - [j1]Idit Diamant, Assaf Hoogi, Christopher F. Beaulieu, Mustafa Safdari, Eyal Klang, Michal Amitai, Hayit Greenspan, Daniel L. Rubin:
Improved Patch-Based Automated Liver Lesion Classification by Separate Analysis of the Interior and Boundary Regions. IEEE J. Biomed. Health Informatics 20(6): 1585-1594 (2016) - [i1]Assaf Hoogi, Christopher F. Beaulieu, Guilherme M. Cunha, Elhamy Heba, Claude B. Sirlin, Sandy Napel, Daniel L. Rubin:
Adaptive Local Window for Level Set Segmentation of CT and MRI Liver Lesions. CoRR abs/1606.03765 (2016) - 2015
- [c2]Yixuan Yuan, Assaf Hoogi, Christopher F. Beaulieu, Max Q.-H. Meng, Daniel L. Rubin:
Weighted locality-constrained linear coding for lesion classification in CT images. EMBC 2015: 6362-6365 - 2013
- [c1]Assaf Hoogi, Grigoriy Zurakhov, Dan Adam:
Evaluation of a 3D technique for quantifying neovascularization within plaques imaged by contrast enhanced ultrasound. EMBC 2013: 1124-1127
Coauthor Index
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