Auto-Generating Weak Labels for Real & Synthetic Data to Improve Label-Scarce Medical Image Segmentation

25 April 2024

Papers citing "Auto-Generating Weak Labels for Real & Synthetic Data to Improve Label-Scarce Medical Image Segmentation"

3 / 3 papers shown

Title
U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation Jun Ma Feifei Li Bo Wang Mamba 80 329 0 09 Jan 2024
Zero-shot performance of the Segment Anything Model (SAM) in 2D medical imaging: A comprehensive evaluation and practical guidelines C. M. Oliveira L. V. Moura R. Ravazio L. S. Kupssinskü Otávio Parraga Marcelo Mussi Delucis Rodrigo C. Barros VLM MedIm 73 26 0 28 Apr 2023
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 232 75,445 0 18 May 2015