AIMC Topic: Image Processing, Computer-Assisted
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BrainNet-GAN: Generative Adversarial Graph Convolutional Network for Functional Brain Network Synthesis from Routine Clinical Brain Structural T1-Weighted Sequence.
Brain topography
Jun 23, 2025
Functional brain network (FBN) derived from functional Magnetic Resonance Imaging (fMRI) has promising prospects in clinical research, but fMRI is not a routine acquisition data, which limits its popularity in clinical applications. Therefore, it is ...
Deep generative models for Bayesian inference on high-rate sensor data: applications in automotive radar and medical imaging.
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Jun 19, 2025
Deep generative models (DGMs) have been studied and developed primarily in the context of natural images and computer vision. This has spurred the development of (Bayesian) methods that use these generative models for inverse problems in image restor...
Exploratory multi-cohort, multi-reader study on the clinical utility of a deep learning model for transforming cryosectioned to formalin-fixed, paraffin-embedded (FFPE) images in breast lesion diagnosis.
Breast cancer research : BCR
Jun 17, 2025
BACKGROUND: Cryosectioned tissues often exhibit artifacts that compromise pathologists' diagnostic accuracy during intraoperative assessments. These inconsistencies, compounded by variations in frozen section (FS) production across laboratories, high...
Quasi-supervised MR-CT image conversion based on unpaired data.
Physics in medicine and biology
Jun 17, 2025
. In radiotherapy planning, acquiring both magnetic resonance (MR) and computed tomography (CT) images is crucial for comprehensive evaluation and treatment. However, simultaneous acquisition of MR and CT images is time-consuming, economically expens...
Enhancing image quality in fast neutron-based range verification of proton therapy using a deep learning-based prior in LM-MAP-EM reconstruction.
Physics in medicine and biology
Jun 17, 2025
This study investigates the use of list-mode (LM) maximum(MAP) expectation maximization (EM) incorporating prior information predicted by a convolutional neural network for image reconstruction in fast neutron (FN)-based proton therapy range verifica...
Research on the correlation between retinal vascular parameters and axial length in children using an AI-based fundus image analysis system.
PloS one
Jun 17, 2025
OBJECTIVE: This study aims to utilize artificial intelligence technology to conduct an in-depth analysis of fundus data from myopic children and adolescents, thoroughly exploring the correlation between retinal vascular parameters and axial length (A...
Semi-automated high content analysis of pollen performance using tubetracker.
Plant reproduction
Jun 16, 2025
TubeTracker provides a method to partially automate analysis of pollen tube growth using live imaging. Pollen function is critical for successful plant reproduction and crop productivity and it is important to develop accessible methods to quantitati...
Fast and accurate lung cancer subtype classication and localization based on Intraoperative frozen sections of lung adenocarcinoma.
Biomedical physics & engineering express
Jun 16, 2025
Current lung cancer diagnostic techniques primarily focus on tissue subtype classification, yet remain inadequate in distinguishing pathological progression subtypes (particularly between adenocarcinomaand invasive adenocarcinoma) on frozen sections....
MRI super-resolution reconstruction using efficient diffusion probabilistic model with residual shifting.
Physics in medicine and biology
Jun 16, 2025
Magnetic resonance imaging (MRI) is essential in clinical and research contexts, providing exceptional soft-tissue contrast. However, prolonged acquisition times often lead to patient discomfort and motion artifacts. Diffusion-based deep learning sup...
A method for feature division of Soccer Foul actions based on salience image semantics.
PloS one
Jun 13, 2025
The purpose of this study is to realize the automatic identification and classification of fouls in football matches and improve the overall identification accuracy. Therefore, a Deep Learning-Based Saliency Prediction Model (DLSPM) is proposed. DLSP...
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