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Found 7 papers, 2 papers with code
Detection-Guided Deep Learning-Based Model with Spatial Regularization for Lung Nodule Segmentation
The segmentation of lung nodules plays a critical role in aiding physicians in distinguishing between malignant and benign lesions.
Novel adaptation of video segmentation to 3D MRI: efficient zero-shot knee segmentation with SAM2
Intelligent medical image segmentation methods are rapidly evolving and being increasingly applied, yet they face the challenge of domain transfer, where algorithm performance degrades due to different data distributions between source and target domains.
Interpretable Small Training Set Image Segmentation Network Originated from Multi-Grid Variational Model
The main objective of image segmentation is to divide an image into homogeneous regions for further analysis.
Improved walker population control for full configuration interaction quantum Monte Carlo
Full configuration interaction quantum Monte Carlo (FCIQMC) is a stochastic approach for finding the ground state of a quantum many-body Hamiltonian.
Quantum Gases Computational Physics
The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset
Purpose: To organize a knee MRI segmentation challenge for characterizing the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring osteoarthritis progression.
Game of Learning Bloch Equation Simulations for MR Fingerprinting
The in vivo T1, T2 maps generated from the GAN-MRF fingerprints are in good agreement with those generated from the Bloch simulated fingerprints, showing good performance and robustness of the proposed GAN-MRF model.
Compressive hyperspectral imaging via adaptive sampling and dictionary learning
In this paper, we propose a new sampling strategy for hyperspectral signals that is based on dictionary learning and singular value decomposition (SVD).
