8 papers · 1 filter
Energy-Based Prior Latent Space Diffusion model for Reconstruction of Lumbar Vertebrae from Thick Slice MRI
Yanke Wang, Yolanne Y. R. Lee, Aurelio Dolfini +3
Lumbar spine problems are ubiquitous, motivating research into targeted imaging for treatment planning and guided interventions. While high resolution and high contrast CT has been…
Image Segmentation in Foundation Model Era: A Survey
Tianfei Zhou, Wang Xia, Fei Zhang +5
Image segmentation is a long-standing challenge in computer vision, studied continuously over several decades, as evidenced by seminal algorithms such as N-Cut, FCN, and MaskFormer…
Diffusion-Based Semantic Segmentation of Lumbar Spine MRI Scans of Lower Back Pain Patients
Maria Monzon, Thomas Iff, Ender Konukoglu +1
This study introduces a diffusion-based framework for robust and accurate segmenton of vertebrae, intervertebral discs (IVDs), and spinal canal from Magnetic Resonance Imaging~(MRI…
Generalizable Single-Source Cross-modality Medical Image Segmentation via Invariant Causal Mechanisms
Boqi Chen, Yuanzhi Zhu, Yunke Ao +5
Single-source domain generalization (SDG) aims to learn a model from a single source domain that can generalize well on unseen target domains. This is an important task in computer…
Do Vision Foundation Models Enhance Domain Generalization in Medical Image Segmentation?
Kerem Cekmeceli, Meva Himmetoglu, Guney I. Tombak +3
Neural networks achieve state-of-the-art performance in many supervised learning tasks when the training data distribution matches the test data distribution. However, their perfor…
Implicit-Zoo: A Large-Scale Dataset of Neural Implicit Functions for 2D Images and 3D Scenes
Qi Ma, Danda Pani Paudel, Ender Konukoglu +1
Neural implicit functions have demonstrated significant importance in various areas such as computer vision, graphics. Their advantages include the ability to represent complex sha…