Titlebook: Information Processing in Medical Imaging; 27th International C Aasa Feragen,Stefan Sommer,Mads Nielsen Conference proceedings 2021 Springe

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Deep Learning Based Geometric Registration for Medical Images: How Accurate Can We Get Without Visualoopy belief message passing to enable highly accurate 3D point cloud registration. Our experimental validation is conducted on complex key-point graphs of inner lung structures, strongly outperforming dense encoder-decoder networks and other point set registration methods. Our code is publicly avai

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敌手

Multiple-Shooting Adjoint Method for Whole-Brain Dynamic Causal Modelings, and is suitable for large-scale systems such as whole-brain analysis in functional MRI (fMRI). Furthermore, MSA uses the adjoint method for accurate gradient estimation in the ODE; since the adjoint method is generic, MSA is a generic method for both linear and non-linear systems, and does not re

obsession

无能力

Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial Trainingrated that our approach, with less training overhead, achieves superior performance over state-of-the-art auto-augmentation methods on both tasks of 2D skin cancer classification and 3D organs-at-risk segmentation.

macular-edema

Blind Stain Separation Using Model-Aware Generative Learning and Its Applications on Fluorescence Mir more, a training algorithm is innovated for the proposed framework to avoid inter-generator confusion during learning. This paper particularly takes fluorescence unmixing in fluorescence microscopy images as an application example of the proposed framework. Qualitative and quantitative experimenta

beta-cells

MR Slice Profile Estimation by Learning to Match Internal Patch Distributionsy, the slice selection profile can be learned without any external data. Our algorithm was tested using simulations from isotropic MR images, incorporated in a through-plane super-resolution algorithm to demonstrate its benefits, and also used as a tool to measure image resolution. Our code is at ..

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theta-waves

Hierarchical Morphology-Guided Tooth Instance Segmentation from CBCT Imagesary tasks. Extensive evaluations, ablation studies, and comparisons with existing methods show that our approach achieved state-of-the-art segmentation performance, especially around the challenging dental parts (i.e., tooth roots and boundaries). These results suggest the potential applicability of