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Learning dissection trajectories from expert surgical videos via imitation learning with equivariant diffusion
Although deep learning-based approaches have demonstrated significant potential in surgical scene analysis (Maier-Hein et ...
Driven by textual knowledge: A Text-View Enhanced Knowledge Transfer Network for lung infection region segmentation
Pneumonia is a prevalent respiratory disease, with cases surging since the COVID-19 pandemic. Infected lung regions typica...
AdaptFRCNet: Semi-supervised adaptation of pre-trained model with frequency and region consistency for medical image segmentation
Medical image segmentation involves delineating anatomical structures, organs, or lesions from medical images to facilitat...
Nested hierarchical group-wise registration with a graph-based subgrouping strategy for efficient template construction
Population-level analysis is an essential task in brain research. Recent studies have investigated brain development and a...
REPAIR: Reciprocal assistance imputation-representation learning for glioma diagnosis with incomplete MRI sequences
Glioma (GM) is the most common malignant primary brain tumor, accounting for approximately 24% of all primary brain and ot...
Next-generation surgical navigation: Marker-less multi-view 6DoF pose estimation of surgical instruments
Computer-assisted interventions have benefited significantly from advances in computer vision (Mascagni et al., 2022) to i...
A survey of deep-learning-based radiology report generation using multimodal inputs
Automatic radiology report generation can alleviate the workload for physicians and minimize regional disparities in medic...
Generating realistic single-cell images from CellProfiler representations
High-throughput data have become an essential tool for uncovering the mechanisms of cellular diseases (O’Reilly et al., 20...
Automated motor-leg scoring in stroke via a stable graph causality debiasing model
Stroke is a leading cause of death and disability worldwide, significantly threatening human health (Feigin et al., 2022; ...
Learning contrast and content representations for synthesizing magnetic resonance image of arbitrary contrast
Magnetic Resonance Imaging (MRI) is an indispensable tool in modern medical diagnosis and intervention, offering non-invas...
An orchestration learning framework for ultrasound imaging: Prompt-Guided Hyper-Perception and Attention-Matching Downstream Synchronization
Ultrasound imaging has become an essential tool in clinical diagnostics due to its affordability, portability, safety (bei...
ScanAhead: Simplifying standard plane acquisition of fetal head ultrasound
The fetal standard plane acquisition task aims to detect an Ultrasound (US) image characterized by specified anatomical la...
Multi-view hybrid graph convolutional network for volume-to-mesh reconstruction in cardiovascular MRI
Cardiovascular magnetic resonance (CMR) imaging has become an indispensable tool in the diagnosis, treatment planning, and...
Efficient few-shot medical image segmentation via self-supervised variational autoencoder
Medical image segmentation is the process of partitioning images, such as Magnetic Resonance Imaging (MRI) and Computed To...
HGMSurvNet: A two-stage hypergraph learning network for multimodal cancer survival prediction
Survival prediction is a crucial task in computational pathology, which aims to analyze the expected duration of time unti...
Enhancing super-resolution ultrasound localisation through multi-frame deconvolution exploiting spatiotemporal consistency
KeywordsUltrasound localisation microscopy (ULM)Super-resolution ultrasound (SRUS)Microbubble contrast agentsDeconvolution...