Frontiers

Universal medical image segmentation via in-context cross-attention

Semantic segmentation is critical in medical image processing, with traditional specialist models facing adaptation challenges to new tasks or distribution shifts. While both generalist pre-trained ...
IEEE

Unsupervised Brain Lesion Segmentation Using Posterior Distributions Learned by Subspace-based Generative Model

Abstract: Unsupervised brain lesion segmentation, focusing on learning normative distributions from images of healthy subjects, are less dependent on lesion-labeled data, thus exhibiting better ...
Scientific Research Publishing

From U-Net to Swin-Unet Transformers: The Next-Generation Advances in Brain Tumor Segmentation with Deep Learning ()

Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving from the ...
Scientific Research Publishing

Minaee, S., Boykov, Y.Y., Porikli, F., Plaza, A.J., Kehtarnavaz, N. and Terzopoulos, D. (2021) Image Segmentation Using Deep Learning: A Survey. IEEE Transactions on Pattern ...

ABSTRACT: In this paper, a novel multilingual OCR (Optical Character Recognition) method for scanned papers is provided. Current open-source solutions, like Tesseract, offer extremely high accuracy ...
Frontiers

GA-TongueNet: tongue image segmentation network using innovative DiFP and MDi for stable generalization ability

1 College of Information Science and Engineering, Henan University of Technology, Zhengzhou, China 2 Institute for Complexity Science, Henan University of Technology, Zhengzhou, China Tongue is ...