IEEE

JOANet: An Integrated Joint Optimization Architecture Making Medical Image Segmentation Really Helped by Super-Resolution Pre-Processing

Abstract: Conventional computer vision pipelines typically treat low-level enhancement and high-level semantic tasks as isolated processes, focusing on optimizing enhancement for perceptual quality ...
IEEE

OpenVocabCT: Towards Universal Text-driven CT Image Segmentation

Abstract: Computed tomography (CT) is extensively used for accurate visualization and segmentation of organs and lesions. While deep learning models such as convolutional neural networks (CNNs) and ...
EurekAlert!

Artificial intelligence for organelle segmentation in live-cell imaging

Recently, Assoc. Prof. Bo Peng (Northwestern Polytechnical University) and Prof. Lin Li (Xiamen University), et ...
Communications of the ACM

Where Are the City Trees? Monitoring Urban Trees across the U.S. Using Generative AI

The use of generative AI enables a novel computational approach to localize individual trees in all cities, despite their ...
IEEE

Distillation-SAM: Knowledge Distillation Based Auto-prompt Embedding Learning for Surgical Image Segmentation

Abstract: Surgical image segmentation is vital for various stages of surgical procedures, from preoperative planning to real-time navigation and postoperative assessment. Despite advances in deep ...
IEEE

UHCT-Net: A Unified Hybrid CNN–Transformer Network for Nasal CT Segmentation and Tumor Analysis

Abstract: Accurate segmentation and tumor identification in the nasal cavity and paranasal sinuses based on three-dimensional computed tomography (3D CT) scans remain a challenging task even today ...