Scribbleprompt: fast and flexible interactive segmentation for any biomedical image

HE Wong, M Rakic, J Guttag, AV Dalca - European Conference on …, 2024 - Springer
Biomedical image segmentation is a crucial part of both scientific research and clinical care.
With enough labelled data, deep learning models can be trained to accurately automate …

MultiverSeg: Scalable Interactive Segmentation of Biomedical Imaging Datasets with In-Context Guidance

HE Wong, JJG Ortiz, J Guttag, AV Dalca - arxiv preprint arxiv:2412.15058, 2024 - arxiv.org
Medical researchers and clinicians often need to perform novel segmentation tasks on a set
of related images. Existing methods for segmenting a new dataset are either interactive …

From Few to More: Scribble-based Medical Image Segmentation via Masked Context Modeling and Continuous Pseudo Labels

Z Wang, Y Ye, Z Chen, M Shu, Y **a - arxiv preprint arxiv:2408.12814, 2024 - arxiv.org
Scribble-based weakly supervised segmentation techniques offer comparable performance
to fully supervised methods while significantly reducing annotation costs, making them an …

Efficient Pan-Cancer Lesion Segmentation from Partially Labeled Data with nnU-Net

Y Kirchhoff, MR Rokuss, B Hamm, A Ravindran… - MICCAI 2024 FLARE … - openreview.net
Accurate segmentation of cancer lesions in whole-body CT scans is essential for diagnosis
and treatment planning. However, this task is challenging due to the diversity of lesion …