AIMC Journal:
Medical image analysis

Showing 261 to 270 of 684 articles

CS-CO: A Hybrid Self-Supervised Visual Representation Learning Method for H&E-stained Histopathological Images.

Medical image analysis Jul 20, 2022
Visual representation extraction is a fundamental problem in the field of computational histopathology. Considering the powerful representation capacity of deep learning and the scarcity of annotations, self-supervised learning has emerged as a promi...
Histological Techniques Supervised Machine Learning Staining and Labeling
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Cardiac MRI segmentation with sparse annotations: Ensembling deep learning uncertainty and shape priors.

Medical image analysis Jul 16, 2022
The performance of deep learning for cardiac magnetic resonance imaging (MRI) segmentation is oftentimes degraded when using small datasets and sparse annotations for training or adapting a pre-trained model to previously unseen datasets. Here, we de...
Magnetic Resonance Imaging Heart Image Processing, Computer-Assisted Uncertainty Deep Learning Humans
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Deep learning solution for medical image localization and orientation detection.

Medical image analysis Jul 6, 2022
Magnetic Resonance (MR) imaging plays an important role in medical diagnosis and biomedical research. Due to the high in-slice resolution and low through-slice resolution nature of MR imaging, the usefulness of the reconstruction highly depends on th...
Algorithms Reproducibility of Results Humans Knee Joint Image Processing, Computer-Assisted Magnetic Resonance Imaging Deep Learning
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Mutual consistency learning for semi-supervised medical image segmentation.

Medical image analysis Jul 6, 2022
In this paper, we propose a novel mutual consistency network (MC-Net+) to effectively exploit the unlabeled data for semi-supervised medical image segmentation. The MC-Net+ model is motivated by the observation that deep models trained with limited a...
Supervised Machine Learning Humans Deep Learning Image Processing, Computer-Assisted
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Unsupervised domain adaptation for clinician pose estimation and instance segmentation in the operating room.

Medical image analysis Jul 3, 2022
The fine-grained localization of clinicians in the operating room (OR) is a key component to design the new generation of OR support systems. Computer vision models for person pixel-based segmentation and body-keypoints detection are needed to better...
Humans Neural Networks, Computer Supervised Machine Learning Operating Rooms Image Processing, Computer-Assisted Software
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Object recognition in medical images via anatomy-guided deep learning.

Medical image analysis Jun 25, 2022
PURPOSE: Despite advances in deep learning, robust medical image segmentation in the presence of artifacts, pathology, and other imaging shortcomings has remained a challenge. In this paper, we demonstrate that by synergistically marrying the unmatch...
Tomography, X-Ray Computed Image Processing, Computer-Assisted Deep Learning Artificial Intelligence Algorithms Humans
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DeepStroke: An efficient stroke screening framework for emergency rooms with multimodal adversarial deep learning.

Medical image analysis Jun 25, 2022
In an emergency room (ER) setting, stroke triage or screening is a common challenge. A quick CT is usually done instead of MRI due to MRI's slow throughput and high cost. Clinical tests are commonly referred to during the process, but the misdiagnosi...
Stroke Emergency Service, Hospital Magnetic Resonance Imaging Triage Deep Learning Humans
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MVFStain: Multiple virtual functional stain histopathology images generation based on specific domain mapping.

Medical image analysis Jun 23, 2022
To the best of our knowledge, artificial intelligence stain generation is an urgent requirement for histopathology images. Pathological examinations usually only utilize hematoxylin and eosin (H&E) regular staining to show histomorphological characte...
Artificial Intelligence Staining and Labeling Humans Eosine Yellowish-(YS) Ki-67 Antigen Coloring Agents
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DARC: Deep adaptive regularized clustering for histopathological image classification.

Medical image analysis Jun 23, 2022
In recent years, deep learning as a state-of-the-art machine learning technique has made great success in histopathological image classification. However, most of deep learning approaches rely heavily on the substantial task-specific annotations, whi...
Neural Networks, Computer Humans Algorithms Machine Learning Cluster Analysis
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Automatic Grading Assessments for Knee MRI Cartilage Defects via Self-ensembling Semi-supervised Learning with Dual-Consistency.

Medical image analysis Jun 18, 2022
Knee cartilage defects caused by osteoarthritis are major musculoskeletal disorders, leading to joint necrosis or even disability if not intervened at early stage. Deep learning has demonstrated its effectiveness in computer-aided diagnosis, but it i...
Cartilage Diagnosis, Computer-Assisted Supervised Machine Learning Humans Knee Joint Magnetic Resonance Imaging
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