Evaluation of a 3D technique for quantifying neovascularization within plaques imaged by contrast enhanced ultrasound. - Assaf Hoogi; Grigoriy Zurakhov; Dan Adam (EMBC, 2013)

Weighted locality-constrained linear coding for lesion classification in CT images. - Yixuan Yuan; Assaf Hoogi; Christopher F. Beaulieu; Max Q.-H. Meng; Daniel L. Rubin (EMBC, 2015)

Automated classification of brain tumor type in whole-slide digital pathology images using local representative tiles. - Jocelyn Barker; Assaf Hoogi; Adrien Depeursinge; Daniel L. Rubin (Medical Image Anal., 2016)

Improved Patch-Based Automated Liver Lesion Classification by Separate Analysis of the Interior and Boundary Regions. - Idit Diamant; Assaf Hoogi; Christopher F. Beaulieu; Mustafa Safdari; Eyal Klang; Michal Amitai; Hayit Greenspan; Daniel L. Rubin (IEEE J. Biomed. Health Informatics, 2016)

A Fully-Automated Pipeline for Detection and Segmentation of Liver Lesions and Pathological Lymph Nodes. - Assaf Hoogi; John W. Lambert; Yefeng Zheng 001; Dorin Comaniciu; Daniel L. Rubin (CoRR, 2017)

Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions. - Zeynettin Akkus; Alfiia Galimzianova; Assaf Hoogi; Daniel L. Rubin; Bradley J. Erickson (J. Digit. Imaging, 2017)

Adaptive local window for level set segmentation of CT and MRI liver lesions. - Assaf Hoogi; Christopher F. Beaulieu; Guilherme M. Cunha; Elhamy Heba; Claude B. Sirlin; Sandy Napel; Daniel L. Rubin (Medical Image Anal., 2017)

Adaptive Estimation of Active Contour Parameters Using Convolutional Neural Networks and Texture Analysis. - Assaf Hoogi; Arjun Subramaniam; Rishi Veerapaneni; Daniel L. Rubin (IEEE Trans. Medical Imaging, 2017)

Deep Active Lesion Segmentation. - Ali Hatamizadeh; Assaf Hoogi; Debleena Sengupta; Wuyue Lu 001; Brian Wilcox; Daniel L. Rubin; Demetri Terzopoulos (MLMI@MICCAI, 2019)

From voxels to pixels and back: Self-supervision in natural-image reconstruction from fMRI. - Roman Beliy; Guy Gaziv; Assaf Hoogi; Francesca Strappini; Tal Golan; Michal Irani (NeurIPS, 2019)

Self-Attention Capsule Networks for Image Classification. - Assaf Hoogi; Brian Wilcox; Yachee Gupta; Daniel L. Rubin (CoRR, 2019)

Natural Language Generation Model for Mammography Reports Simulation. - Assaf Hoogi; Arjun Mishra; Francisco Gimenez; Jeffrey Dong; Daniel L. Rubin (IEEE J. Biomed. Health Informatics, 2020)

Self-attention Capsule Network for Tissue Classification in Case of Challenging Medical Image Statistics. - Assaf Hoogi; Brian Wilcox; Yachee Gupta; Daniel L. Rubin (ECCV Workshops (3), 2022)

Self-supervised Natural Image Reconstruction and Large-scale Semantic Classification from Brain Activity. - Guy Gaziv; Roman Beliy; Niv Granot; Assaf Hoogi; Francesca Strappini; Tal Golan; Michal Irani (NeuroImage, 2022)

Leveraging the Triple Exponential Moving Average for Fast-Adaptive Moment Estimation. - Roi Peleg; Roi Weiss; Assaf Hoogi (CoRR, 2023)

Unsupervised Iterative U-Net with an Internal Guidance Layer for Vertebrae Contrast Enhancement in Chest X-Ray Images. - Ella Eidlin; Assaf Hoogi; Nathan S. Netanyahu (CoRR, 2023)

Dynamic Group Normalization: Spatio-Temporal Adaptation to Evolving Data Statistics. - Yair Smadar; Assaf Hoogi (CVPR, 2025)