AIMC Topic: Image Interpretation, Computer-Assisted

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Groupwise image registration with edge-based loss for low-SNR cardiac MRI.

Magnetic resonance in medicine
PURPOSE: The purpose of this study is to perform image registration and averaging of multiple free-breathing single-shot cardiac images, where the individual images may have a low signal-to-noise ratio (SNR).

Advancement of an automatic segmentation pipeline for metallic artifact removal in post-surgical ACL MRI.

Magnetic resonance imaging
Magnetic resonance imaging (MRI) has the potential to identify post-operative risk factors for re-tearing an anterior cruciate ligament (ACL) using a combination of imaging signal intensity (SI) and cross-sectional area measurements of the healing AC...

The Development and Evaluation of a Convolutional Neural Network for Cutaneous Melanoma Detection in Whole Slide Images.

Archives of pathology & laboratory medicine
CONTEXT.—: The current melanoma staging system does not account for 26% of the variance seen in melanoma-specific survival, therefore our ability to predict patient outcome is not fully elucidated. Morphology may be of greater significance than in ot...

AI-Assisted Detection Support for Middle Ear Diseases Using Multimodal Large Language Models.

Studies in health technology and informatics
Middle ear diseases, such as otitis media and middle ear effusion, are difficult to accurately detect in primary care. We developed an AI-powered system using Azure OpenAI's GPT-4 Vision, the first multimodal large language model (LLM) applied to ana...

Detecting and Classifying Mycetoma in Histopathological Images Using DenseNet and U-Net.

Studies in health technology and informatics
Mycetoma, recognised by the WHO as a Neglected Tropical Disease, has significant diagnostic hurdles which lead to severe health consequences. Mycetoma can be caused by certain types of bacteria (actinomycetoma) or fungi (eumycetoma). Identifying whet...

Fada: Fetal Accurate Detection AI for Automated Ultrasound Image Analysis and Reporting.

Studies in health technology and informatics
This study introduces Fetal Accurate Detection AI (FADA) an advanced AI-driven framework for generating clinically relevant descriptions from fetal ultrasound images, specifically focused on diverse anatomical structures and views, including trans-ab...

Effect of Deep Learning-Based Artificial Intelligence on Radiologists' Performance in Identifying Nigrosome 1 Abnormalities on Susceptibility Map-Weighted Imaging.

Korean journal of radiology
OBJECTIVE: To evaluate the effect of deep learning (DL)-based artificial intelligence (AI) software on the diagnostic performance of radiologists with different experience levels in detecting nigrosome 1 (N1) abnormalities on susceptibility map-weigh...

LGF-Net: A multi-scale feature fusion network for thyroid nodule ultrasound image classification.

Journal of applied clinical medical physics
BACKGROUND: Thyroid cancer is one of the most common cancers in clinical practice, and accurate classification of thyroid nodule ultrasound images is crucial for computer-aided diagnosis. Models based on a convolutional neural network (CNN) or a tran...

[AI-based applications in medical image computing].

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
The processing of medical images plays a central role in modern diagnostics and therapy. Automated processing and analysis of medical images can efficiently accelerate clinical workflows and open new opportunities for improved patient care. However, ...

Certainty-Guided Cross Contrastive Learning for Semi-Supervised Medical Image Segmentation.

IEEE transactions on bio-medical engineering
Semi-supervised learning (SSL) enables the accurate segmentation of medical images with limited available labeled data. However, its performance usually lags fully supervised methods that require the whole dataset to be labeled. We propose a novel SS...