AIMC Journal:
Medical image analysis

Showing 241 to 250 of 684 articles

A semi-supervised multi-task learning framework for cancer classification with weak annotation in whole-slide images.

Medical image analysis Oct 14, 2022
Cancer region detection (CRD) and subtyping are two fundamental tasks in digital pathology image analysis. The development of data-driven models for CRD and subtyping on whole-slide images (WSIs) would mitigate the burden of pathologists and improve ...
Head Supervised Machine Learning Neoplasms Humans
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A review on deep-learning algorithms for fetal ultrasound-image analysis.

Medical image analysis Oct 14, 2022
Deep-learning (DL) algorithms are becoming the standard for processing ultrasound (US) fetal images. A number of survey papers in the field is today available, but most of them are focusing on a broader area of medical-image analysis or not covering ...
Humans Deep Learning
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Predicting the evolution trajectory of population-driven connectional brain templates using recurrent multigraph neural networks.

Medical image analysis Oct 7, 2022
The mapping of the time-dependent evolution of the human brain connectivity using longitudinal and multimodal neuroimaging datasets provides insights into the development of neurological disorders and the way they alter the brain morphology, structur...
Neural Networks, Computer Brain Humans
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IFT-Net: Interactive Fusion Transformer Network for Quantitative Analysis of Pediatric Echocardiography.

Medical image analysis Sep 29, 2022
The task of automatic segmentation and measurement of key anatomical structures in echocardiography is critical for subsequent extraction of clinical parameters. However, the influence of boundary blur, speckle noise, and other factors increase the d...
Heart Ventricles Neural Networks, Computer Child Echocardiography Image Processing, Computer-Assisted Humans Heart
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Towards annotation-efficient segmentation via image-to-image translation.

Medical image analysis Sep 21, 2022
An important challenge and limiting factor in deep learning methods for medical imaging segmentation is the lack of available of annotated data to properly train models. For the specific task of tumor segmentation, the process entails clinicians labe...
Deep Learning Magnetic Resonance Imaging Image Processing, Computer-Assisted Humans Neural Networks, Computer Neoplasm, Residual
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Gaze-assisted automatic captioning of fetal ultrasound videos using three-way multi-modal deep neural networks.

Medical image analysis Sep 17, 2022
In this work, we present a novel gaze-assisted natural language processing (NLP)-based video captioning model to describe routine second-trimester fetal ultrasound scan videos in a vocabulary of spoken sonography. The primary novelty of our multi-mod...
Humans Ultrasonography, Prenatal Neural Networks, Computer Pregnancy Female Algorithms
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TransMorph: Transformer for unsupervised medical image registration.

Medical image analysis Sep 14, 2022
In the last decade, convolutional neural networks (ConvNets) have been a major focus of research in medical image analysis. However, the performances of ConvNets may be limited by a lack of explicit consideration of the long-range spatial relationshi...
Magnetic Resonance Imaging Bayes Theorem Image Processing, Computer-Assisted Phantoms, Imaging Humans Imaging, Three-Dimensional Neural Networks, Computer
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Domain generalization for prostate segmentation in transrectal ultrasound images: A multi-center study.

Medical image analysis Sep 13, 2022
Prostate biopsy and image-guided treatment procedures are often performed under the guidance of ultrasound fused with magnetic resonance images (MRI). Accurate image fusion relies on accurate segmentation of the prostate on ultrasound images. Yet, th...
Neural Networks, Computer Male Humans Pelvis Ultrasonography Magnetic Resonance Imaging Prostate
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Beyond fine-tuning: Classifying high resolution mammograms using function-preserving transformations.

Medical image analysis Sep 6, 2022
The task of classifying mammograms is very challenging because the lesion is usually small in the high resolution image. The current state-of-the-art approaches for medical image classification rely on using the de-facto method for convolutional neur...
Mammography Humans Neural Networks, Computer
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Anticipation for surgical workflow through instrument interaction and recognized Signals.

Medical image analysis Sep 6, 2022
Surgical workflow anticipation is an essential task for computer-assisted intervention (CAI) systems. It aims at predicting the future surgical phase and instrument occurrence, providing support for intra-operative decision-support system. Recent stu...
Artifacts Surgical Instruments Workflow Humans Image Processing, Computer-Assisted Neural Networks, Computer
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