Efficient Low-Dose CT Denoising by Locally-Consistent Non-Local Means (LC-NLM). - Michael Green; Edith M. Marom; Nahum Kiryati; Eli Konen; Arnaldo Mayer (MICCAI (3), 2016)

A Neural Regression Framework for Low-Dose Coronary CT Angiography (CCTA) Denoising. - Michael Green; Edith M. Marom; Nahum Kiryati; Eli Konen; Arnaldo Mayer (Patch-MI@MICCAI, 2017)

Patient-specific image denoising for ultra-low-dose CT-guided lung biopsies. - Michael Green; Edith M. Marom; Eli Konen; Nahum Kiryati; Arnaldo Mayer (Int. J. Comput. Assist. Radiol. Surg., 2017)

Learning Real Noise for Ultra-Low Dose Lung CT Denoising. - Michael Green; Edith M. Marom; Eli Konen; Nahum Kiryati; Arnaldo Mayer (Patch-MI@MICCAI, 2018)

3-D Neural denoising for low-dose Coronary CT Angiography (CCTA). - Michael Green; Edith M. Marom; Eli Konen; Nahum Kiryati; Arnaldo Mayer (Comput. Medical Imaging Graph., 2018)

Feature Aggregation in Perceptual Loss for Ultra Low-Dose (ULD) CT Denoising. - Michael Green; Edith M. Marom; Eli Konen; Nahum Kiryati; Arnaldo Mayer (ISBI, 2019)

RV strain classification from 3D CTPA scans using weakly supervised residual attention model. - Noa Cahan; Edith M. Marom; Shelly Soffer; Yiftach Barash; Eli Konen; Eyal Klang; Hayit Greenspan (Computer-Aided Diagnosis, 2021)

Weakly Supervised Attention Model for RV StrainClassification from volumetric CTPA Scans. - Noa Cahan; Edith M. Marom; Shelly Soffer; Yiftach Barash; Eli Konen; Eyal Klang; Hayit Greenspan (CoRR, 2021)

Weakly Supervised Multimodal 30-Day All-Cause Mortality Prediction for Pulmonary Embolism Patients. - Noa Cahan; Edith M. Marom; Shelly Soffer; Yiftach Barash; Eli Konen; Eyal Klang; Hayit Greenspan (ISBI, 2022)

Weakly supervised attention model for RV strain classification from volumetric CTPA scans. - Noa Cahan; Edith M. Marom; Shelly Soffer; Yiftach Barash; Eli Konen; Eyal Klang; Hayit Greenspan (Comput. Methods Programs Biomed., 2022)

Perceptual Transformer Loss for the Neural Denoising of Ultra-Low Dose CT. - Michael Green; Edith M. Marom; Arnaldo Mayer (ISBI, 2024)