AIMC Topic: Image Interpretation, Computer-Assisted
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AI-based assessment of longitudinal multiple sclerosis MRI: Strengths and weaknesses in clinical practice.
European journal of radiology
Jan 18, 2025
OBJECTIVES: In Multiple Sclerosis (MS) cerebral MRI is essential for disease and treatment monitoring. For this purpose, software solutions are available to support the radiologist with image interpretation and reporting of follow up imaging. Aim of ...
TagGen: Diffusion-based generative model for cardiac MR tagging super resolution.
Magnetic resonance in medicine
Jan 17, 2025
PURPOSE: The aim of the work is to develop a cascaded diffusion-based super-resolution model for low-resolution (LR) MR tagging acquisitions, which is integrated with parallel imaging to achieve highly accelerated MR tagging while enhancing the tag g...
Enhanced AMD detection in OCT images using GLCM texture features with Machine Learning and CNN methods.
Biomedical physics & engineering express
Jan 17, 2025
Global blindness is substantially influenced by age-related macular degeneration (AMD). It significantly shortens people's lives and severely impairs their visual acuity. AMD is becoming more common, requiring improved diagnostic and prognostic metho...
Application of cloud server-based machine learning for assisting pathological structure recognition in IgA nephropathy.
Journal of clinical pathology
Jan 17, 2025
BACKGROUND: Machine learning (ML) models can help assisting diagnosis by rapidly localising and classifying regions of interest (ROIs) within whole slide images (WSIs). Effective ML models for clinical decision support require a substantial dataset o...
Physical Color Calibration of Digital Pathology Scanners for Robust Artificial Intelligence-Assisted Cancer Diagnosis.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Jan 16, 2025
The potential of artificial intelligence (AI) in digital pathology is limited by technical inconsistencies in the production of whole slide images (WSIs). This causes degraded AI performance and poses a challenge for widespread clinical application, ...
ResViT FusionNet Model: An explainable AI-driven approach for automated grading of diabetic retinopathy in retinal images.
Computers in biology and medicine
Jan 16, 2025
BACKGROUND AND OBJECTIVE: Diabetic Retinopathy (DR) is a serious diabetes complication that can cause blindness if not diagnosed in its early stages. Manual diagnosis by ophthalmologists is labor-intensive and time-consuming, particularly in overburd...
Adapting to evolving MRI data: A transfer learning approach for Alzheimer's disease prediction.
NeuroImage
Jan 16, 2025
Integrating 3D magnetic resonance imaging (MRI) with machine learning has shown promising results in healthcare, especially in detecting Alzheimer's Disease (AD). However, changes in MRI technologies and acquisition protocols often yield limited data...
Predicting Paediatric Brain Disorders from MRI Images Using Advanced Deep Learning Techniques.
Neuroinformatics
Jan 16, 2025
The problem at hand is the significant global health challenge posed by children's diseases, where timely and accurate diagnosis is crucial for effective treatment and management. Conventional diagnosis techniques are typical, use tedious processes a...
Investigating the key principles in two-step heterogeneous transfer learning for early laryngeal cancer identification.
Scientific reports
Jan 16, 2025
Data scarcity in medical images makes transfer learning a common approach in computer-aided diagnosis. Some disease classification tasks can rely on large homogeneous public datasets to train the transferred model, while others cannot, i.e., endoscop...
UnICLAM: Contrastive representation learning with adversarial masking for unified and interpretable Medical Vision Question Answering.
Medical image analysis
Jan 15, 2025
Medical Visual Question Answering aims to assist doctors in decision-making when answering clinical questions regarding radiology images. Nevertheless, current models learn cross-modal representations through residing vision and text encoders in dual...
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