AIMC Topic: Image Interpretation, Computer-Assisted
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Selection of Dataframes Presenting Glioma from Magnetic Resonance Images: a Deep Learning Approach.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Due to its complexity and time-consuming nature, identifying gliomas at the Magnetic Resonance Imaging (MRI) slice-level before segmentation could assist clinicians in minimizing the time required for this procedure. In the literature, many studies p...
Ensemble Distillation of Divergent Opinions for Robust Pathological Image Classification.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
The construction of highly accurate deep neural networks (DNNs) requires consistent labeled data. However, there are numerous cases wherein the ground truth is not uniquely determined, even for the same data, owing to different interpretations depend...
Weakly Supervised Deep Learning in Radiology.
Radiology
Jul 1, 2024
Deep learning (DL) is currently the standard artificial intelligence tool for computer-based image analysis in radiology. Traditionally, DL models have been trained with strongly supervised learning methods. These methods depend on reference standard...
Potential Role of Generative Adversarial Networks in Enhancing Brain Tumors.
JCO clinical cancer informatics
Jul 1, 2024
PURPOSE: Contrast enhancement is necessary for visualizing, diagnosing, and treating brain tumors. Through this study, we aimed to examine the potential role of general adversarial neural networks in generating artificial intelligence-based enhanceme...
Stepwise Transfer Learning for Expert-level Pediatric Brain Tumor MRI Segmentation in a Limited Data Scenario.
Radiology. Artificial intelligence
Jul 1, 2024
Purpose To develop, externally test, and evaluate clinical acceptability of a deep learning pediatric brain tumor segmentation model using stepwise transfer learning. Materials and Methods In this retrospective study, the authors leveraged two T2-wei...
Deep Learning Prostate MRI Segmentation Accuracy and Robustness: A Systematic Review.
Radiology. Artificial intelligence
Jul 1, 2024
Purpose To investigate the accuracy and robustness of prostate segmentation using deep learning across various training data sizes, MRI vendors, prostate zones, and testing methods relative to fellowship-trained diagnostic radiologists. Materials and...
Prognostication of Hepatocellular Carcinoma Using Artificial Intelligence.
Korean journal of radiology
Jun 1, 2024
Hepatocellular carcinoma (HCC) is a biologically heterogeneous tumor characterized by varying degrees of aggressiveness. The current treatment strategy for HCC is predominantly determined by the overall tumor burden, and does not address the diverse ...
Deformation-encoding Deep Learning Transformer for High-Frame-Rate Cardiac Cine MRI.
Radiology. Cardiothoracic imaging
Jun 1, 2024
Purpose To develop a deep learning model for increasing cardiac cine frame rate while maintaining spatial resolution and scan time. Materials and Methods A transformer-based model was trained and tested on a retrospective sample of cine images from 5...
AI Approach for Enhanced Thalassemia Diagnosis Using Blood Smear Images.
Studies in health technology and informatics
May 23, 2024
This paper aims to propose an approach leveraging Artificial Intelligence (AI) to diagnose thalassemia through medical imaging. The idea is to employ a U-net neural network architecture for precise erythrocyte morphology detection and classification ...
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