15 citations · 18 across the 6 of their papers we have counts for
7 papers
MIP-Based Tumor Segmentation: A Radiologist-Inspired Approach
Romario Zarik, Nahum Kiryati, Michael Green +2
PET/CT imaging is the gold standard for tumor detection, offering high accuracy in identifying local and metastatic lesions. Radiologists often begin assessment with rotational Mul…
Automatic Breast Lesion Classification by Joint Neural Analysis of Mammography and Ultrasound
Gavriel Habib, Nahum Kiryati, Miri Sklair-Levy +6
Mammography and ultrasound are extensively used by radiologists as complementary modalities to achieve better performance in breast cancer diagnosis. However, existing computer-aid…
Labeling of Multilingual Breast MRI Reports
Chen-Han Tsai, Nahum Kiryati, Eli Konen +2
Medical reports are an essential medium in recording a patient's condition throughout a clinical trial. They contain valuable information that can be extracted to generate a large…
Knee Injury Detection using MRI with Efficiently-Layered Network (ELNet)
Chen-Han Tsai, Nahum Kiryati, Eli Konen +2
Magnetic Resonance Imaging (MRI) is a widely-accepted imaging technique for knee injury analysis. Its advantage of capturing knee structure in three dimensions makes it the ideal t…
Dataset Growth in Medical Image Analysis Research
Yuval Landau, Nahum Kiryati
Medical image analysis studies usually require medical image datasets for training, testing and validation of algorithms. The need is underscored by the deep learning revolution an…
Fast and easy blind deblurring using an inverse filter and PROBE
Naftali Zon, Rana Hanocka, Nahum Kiryati
PROBE (Progressive Removal of Blur Residual) is a recursive framework for blind deblurring. Using the elementary modified inverse filter at its core, PROBE's experimental performan…