Titlebook: Information Processing in Medical Imaging; 28th International C Alejandro Frangi,Marleen de Bruijne,Nassir Navab Conference proceedings 202

沙漠

Meta-information-Aware Dual-path Transformer for Differential Diagnosis of Multi-type Pancreatic Lesth). The S-path focuses on initial feature extraction by semantic segmentation using a UNet-based network. The C-path utilizes both the extracted features and meta-information for patient-level classification based on stacks of dual-path transformer blocks that enhance the modeling of global context

GROSS

MetaViT: Metabolism-Aware Vision Transformer for Differential Diagnosis of Parkinsonism with ,F-FDG el metabolism-aware vision transformer (MetaViT), which uses self-attention and convolution to explicitly characterize both global and local metabolic interactions between interrelated brain regions. A masked image reconstruction task is introduced to guide the MetaViT model to focus on disease-rela

Mendacious

含沙射影

Pixel-Level Explanation of Multiple Instance Learning Models in Biomedical Single Cell Images cells. Additionally, we compare attribution maps with the annotations of a medical expert to see how the model’s decision-making differs from the human standard. Our study addresses the challenge of implementing pixel-level explainability in multiple instance learning models and provides insights f

Generic-Drug

Transient Hemodynamics Prediction Using an Efficient Octree-Based Deep Learning Modelels. In this work, we present an architecture that is tailored to predict high-resolution (spatial and temporal) velocity fields for complex synthetic vascular geometries. For this, an octree-based spatial discretization is combined with an implicit neural function representation to efficiently hand

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Tom Nuno Wolf,Sebastian Pölsterl,Christian Wachinger