Search Results for author: Dafna Ben Bashat

Found 7 papers, 0 papers with code

Contour Dice loss for structures with Fuzzy and Complex Boundaries in Fetal MRI

no code implementations25 Sep 2022 Bella Specktor Fadida, Bossmat Yehuda, Daphna Link Sourani, Liat Ben Sira, Dafna Ben Bashat, Leo Joskowicz

In this paper, we study the use of the Contour Dice loss for both problems and compare it to other boundary losses and to the combined Dice and Cross-Entropy loss.

Brain Segmentation Placenta Segmentation

Partial annotations for the segmentation of large structures with low annotation cost

no code implementations25 Sep 2022 Bella Specktor Fadida, Daphna Link Sourani, Liat Ben Sira Elka Miller, Dafna Ben Bashat, Leo Joskowicz

We tested the method with the popular soft Dice loss for the fetal body segmentation task in two MRI sequences, TRUFI and FIESTA, and compared full annotation regime to partial annotations with a similar annotation effort.

Automatic fetal fat quantification from MRI

no code implementations8 Sep 2022 Netanell Avisdris, Aviad Rabinowich, Daniel Fridkin, Ayala Zilberman, Sapir Lazar, Jacky Herzlich, Zeev Hananis, Daphna Link-Sourani, Liat Ben-Sira, Liran Hiersch, Dafna Ben Bashat, Leo Joskowicz

It consists of two steps: 1) model-based semi-automatic fetal fat segmentations, reviewed and corrected by a radiologist; 2) automatic fetal fat segmentation using DL networks trained on the resulting annotated dataset.

BiometryNet: Landmark-based Fetal Biometry Estimation from Standard Ultrasound Planes

no code implementations29 Jun 2022 Netanell Avisdris, Leo Joskowicz, Brian Dromey, Anna L. David, Donald M. Peebles, Danail Stoyanov, Dafna Ben Bashat, Sophia Bano

Comparison and cross-validation of three different biometric measurements on two independent datasets shows that BiometryNet is robust and yields accurate measurements whose errors are lower than the clinically permissible errors, outperforming other existing automated biometry estimation methods.

Compressed sensing for longitudinal MRI: An adaptive-weighted approach

no code implementations10 Jul 2014 Lior Weizman, Yonina C. Eldar, Dafna Ben Bashat

Methods: The proposed approach utilizes the possible similarity of the repeated scans in longitudinal MRI studies.

Image Reconstruction

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