AIMC Journal:
Medical image analysis

Showing 161 to 170 of 684 articles

A causality-inspired generalized model for automated pancreatic cancer diagnosis.

Medical image analysis Mar 22, 2024
Pancreatic cancer (PC) is a severely malignant cancer variant with high mortality. Since PC has no obvious symptoms, most PC patients are belatedly diagnosed at advanced disease stages. Recently, artificial intelligence (AI) approaches have demonstra...
Humans Pancreatic Neoplasms Tomography, X-Ray Computed Artificial Intelligence
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Automatic multi-view pose estimation in focused cardiac ultrasound.

Medical image analysis Mar 22, 2024
Focused cardiac ultrasound (FoCUS) is a valuable point-of-care method for evaluating cardiovascular structures and function, but its scope is limited by equipment and operator's experience, resulting in primarily qualitative 2D exams. This study pres...
Humans Heart Echocardiography Neural Networks, Computer Imaging, Three-Dimensional
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CellViT: Vision Transformers for precise cell segmentation and classification.

Medical image analysis Mar 16, 2024
Nuclei detection and segmentation in hematoxylin and eosin-stained (H&E) tissue images are important clinical tasks and crucial for a wide range of applications. However, it is a challenging task due to nuclei variances in staining and size, overlapp...
Cell Nucleus Eosine Yellowish-(YS) Humans Staining and Labeling Image Processing, Computer-Assisted Hematoxylin Neural Networks, Computer
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On the pitfalls of Batch Normalization for end-to-end video learning: A study on surgical workflow analysis.

Medical image analysis Mar 1, 2024
Batch Normalization's (BN) unique property of depending on other samples in a batch is known to cause problems in several tasks, including sequence modeling. Yet, BN-related issues are hardly studied for long video understanding, despite the ubiquito...
Neural Networks, Computer Workflow Humans
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TractGeoNet: A geometric deep learning framework for pointwise analysis of tract microstructure to predict language assessment performance.

Medical image analysis Feb 23, 2024
We propose a geometric deep-learning-based framework, TractGeoNet, for performing regression using diffusion magnetic resonance imaging (dMRI) tractography and associated pointwise tissue microstructure measurements. By employing a point cloud repres...
Brain Young Adult Language Diffusion Magnetic Resonance Imaging Humans Neural Pathways Deep Learning Connectome White Matter
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Mutual learning with reliable pseudo label for semi-supervised medical image segmentation.

Medical image analysis Feb 21, 2024
Semi-supervised learning has garnered significant interest as a method to alleviate the burden of data annotation. Recently, semi-supervised medical image segmentation has garnered significant interest that can alleviate the burden of densely annotat...
Heart Atria Image Processing, Computer-Assisted Supervised Machine Learning Reproducibility of Results Tomography, X-Ray Computed Humans
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Semi-supervised medical image classification via distance correlation minimization and graph attention regularization.

Medical image analysis Feb 21, 2024
We propose a novel semi-supervised learning method to leverage unlabeled data alongside minimal annotated data and improve medical imaging classification performance in realistic scenarios with limited labeling budgets to afford data annotations. Our...
Supervised Machine Learning Benchmarking Neural Networks, Computer Humans
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Social network analysis of cell networks improves deep learning for prediction of molecular pathways and key mutations in colorectal cancer.

Medical image analysis Jan 5, 2024
Colorectal cancer (CRC) is a primary global health concern, and identifying the molecular pathways, genetic subtypes, and mutations associated with CRC is crucial for precision medicine. However, traditional measurement techniques such as gene sequen...
Social Network Analysis Humans Proto-Oncogene Proteins B-raf Microsatellite Instability Deep Learning Mutation Colorectal Neoplasms
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Attention De-sparsification Matters: Inducing diversity in digital pathology representation learning.

Medical image analysis Dec 28, 2023
We propose DiRL, a Diversity-inducing Representation Learning technique for histopathology imaging. Self-supervised learning (SSL) techniques, such as contrastive and non-contrastive approaches, have been shown to learn rich and effective representat...
Image Processing, Computer-Assisted Humans Phenotype Pathology Machine Learning
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Learning image representations for anomaly detection: Application to discovery of histological alterations in drug development.

Medical image analysis Dec 21, 2023
We present a system for anomaly detection in histopathological images. In histology, normal samples are usually abundant, whereas anomalous (pathological) cases are scarce or not available. Under such settings, one-class classifiers trained on health...
Drug Development Humans Neural Networks, Computer
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