AIMC Journal:
Medical image analysis

Showing 251 to 260 of 684 articles

Enhancing MR image segmentation with realistic adversarial data augmentation.

Medical image analysis Aug 28, 2022
The success of neural networks on medical image segmentation tasks typically relies on large labeled datasets for model training. However, acquiring and manually labeling a large medical image set is resource-intensive, expensive, and sometimes impra...
Humans Neural Networks, Computer Male Image Processing, Computer-Assisted Supervised Machine Learning
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UC-NfNet: Deep learning-enabled assessment of ulcerative colitis from colonoscopy images.

Medical image analysis Aug 27, 2022
Ulcerative colitis (UC) belongs to the inflammatory bowel disease (IBD) family, which is mainly caused by inflammation of the tissue in the colon and rectum. The severity of this infection can radically affect the patient's overall well-being. Althou...
Humans Colonoscopy Deep Learning Colitis, Ulcerative Rectum
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A framework for falsifiable explanations of machine learning models with an application in computational pathology.

Medical image analysis Aug 24, 2022
In recent years, deep learning has been the key driver of breakthrough developments in computational pathology and other image based approaches that support medical diagnosis and treatment. The underlying neural networks as inherent black boxes lack ...
Humans Neural Networks, Computer Machine Learning Neoplasms Microscopy
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A survey of catheter tracking concepts and methodologies.

Medical image analysis Aug 22, 2022
Catheter tracking has become an integral part of interventional radiology. Over the last decades, researchers have significantly contributed to theoretical and technical catheter tracking solutions. However, most of the published work thus far focuse...
Humans Magnetic Resonance Imaging Robotics Endovascular Procedures Catheters
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3D vessel-like structure segmentation in medical images by an edge-reinforced network.

Medical image analysis Aug 22, 2022
The vessel-like structure in biomedical images, such as within cerebrovascular and nervous pathologies, is an essential biomarker in understanding diseases' mechanisms and in diagnosing and treating diseases. However, existing vessel-like structure s...
Humans Neural Networks, Computer Algorithms Imaging, Three-Dimensional Image Processing, Computer-Assisted
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Distributed contrastive learning for medical image segmentation.

Medical image analysis Aug 12, 2022
Supervised deep learning needs a large amount of labeled data to achieve high performance. However, in medical imaging analysis, each site may only have a limited amount of data and labels, which makes learning ineffective. Federated learning (FL) ca...
Humans Magnetic Resonance Imaging Supervised Machine Learning
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Gumbel-Softmax based Neural Architecture Search for Hierarchical Brain Networks Decomposition.

Medical image analysis Aug 6, 2022
Understanding the brain's functional architecture has been an important topic in the neuroimaging field. A variety of brain network modeling methods have been proposed. Recently, deep neural network-based methods have shown a great advantage in model...
Humans Neural Networks, Computer Algorithms Brain Magnetic Resonance Imaging Neuroimaging
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Transformer-based unsupervised contrastive learning for histopathological image classification.

Medical image analysis Jul 30, 2022
A large-scale and well-annotated dataset is a key factor for the success of deep learning in medical image analysis. However, assembling such large annotations is very challenging, especially for histopathological images with unique characteristics (...
Humans Neural Networks, Computer Staining and Labeling Supervised Machine Learning Mitosis
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Deep active learning for suggestive segmentation of biomedical image stacks via optimisation of Dice scores and traced boundary length.

Medical image analysis Jul 24, 2022
Manual segmentation of stacks of 2D biomedical images (e.g., histology) is a time-consuming task which can be sped up with semi-automated techniques. In this article, we present a suggestive deep active learning framework that seeks to minimise the a...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Magnetic Resonance Imaging Histological Techniques
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Interpretability-Guided Inductive Bias For Deep Learning Based Medical Image.

Medical image analysis Jul 22, 2022
Deep learning methods provide state of the art performance for supervised learning based medical image analysis. However it is essential that trained models extract clinically relevant features for downstream tasks as, otherwise, shortcut learning an...
Humans Deep Learning Image Processing, Computer-Assisted Diagnostic Imaging
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