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A Soft STAPLE Algorithm Combined with Anatomical Knowledge
Eytan Kats, Jacob Goldberger, Hayit Greenspan
Supervised machine learning algorithms, especially in the medical domain, are affected by considerable ambiguity in expert markings. In this study we address the case where the exp…
Precise Detection in Densely Packed Scenes
Eran Goldman, Roei Herzig, Aviv Eisenschtat +4
Man-made scenes can be densely packed, containing numerous objects, often identical, positioned in close proximity. We show that precise object detection in such scenes remains a c…
Classification and Detection in Mammograms with Weak Supervision via Dual Branch Deep Neural Net
Ran Bakalo, Rami Ben-Ari, Jacob Goldberger
The high cost of generating expert annotations, poses a strong limitation for supervised machine learning methods in medical imaging. Weakly supervised methods may provide a soluti…
Weakly and Semi Supervised Detection in Medical Imaging via Deep Dual Branch Net
Ran Bakalo, Jacob Goldberger, Rami Ben-Ari
This study presents a novel deep learning architecture for multi-class classification and localization of abnormalities in medical imaging illustrated through experiments on mammog…
Aligning Vector-spaces with Noisy Supervised Lexicons
Noa Yehezkel Lubin, Jacob Goldberger, Yoav Goldberg
The problem of learning to translate between two vector spaces given a set of aligned points arises in several application areas of NLP. Current solutions assume that the lexicon w…
Soft labeling by Distilling Anatomical knowledge for Improved MS Lesion Segmentation
Eytan Kats, Jacob Goldberger, Hayit Greenspan
This paper explores the use of a soft ground-truth mask ("soft mask'') to train a Fully Convolutional Neural Network (FCNN) for segmentation of Multiple Sclerosis (MS) lesions. Det…