Accurate Panoptic Segmentation and Labeling of Lumbar Spine Vertebrae using a Modified Attention UNet Architecture
A novel modified attention UNet architecture with enhanced multi-class panoptic segmentation capabilities enables accurate and efficient delineation of lumbar spine vertebrae from 3D MRI data.
Slide-SAM: Efficient 3D Medical Image Segmentation with Sliding Window Approach
Slide-SAM, a novel network that leverages a sliding window approach to efficiently segment 3D medical images with minimal prompts, outperforming existing methods on various benchmarks.
DiffOp-net: A Differential Operator-based Fully Convolutional Network for Efficient and Accurate Unsupervised Deformable Image Registration
The proposed DiffOp-net framework introduces a differential operator into the unsupervised deformable image registration process, ensuring smooth and accurate registration while preserving desirable diffeomorphic properties. It also employs a multi-resolution architecture and a novel cross-coordinate attention module to effectively handle large deformations between image pairs.
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