AIMC Topic: Image Processing, Computer-Assisted

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Artificial intelligence based automatic classification, annotation, and measurement of the fetal heart using HeartAssist.

Scientific reports Apr 16, 2025
This study evaluated the feasibility of HeartAssist, a novel automated tool designed for classification of fetal cardiac views, annotation of cardiac structures, and measurement of cardiac parameters. Unlike previous AI tools that primarily focused o...
Heart Defects, Congenital Fetal Heart Humans Neural Networks, Computer Artificial Intelligence Ultrasonography, Prenatal Pregnancy Image Processing, Computer-Assisted Female Gestational Age
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An interpretable framework for gastric cancer classification using multi-channel attention mechanisms and transfer learning approach on histopathology images.

Scientific reports Apr 16, 2025
The importance of gastric cancer (GC) and the role of deep learning techniques in categorizing GC histopathology images have recently increased. Identifying the drawbacks of traditional deep learning models, including lack of interpretability, inabil...
Deep Learning Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Stomach Neoplasms
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Attention LinkNet-152: a novel encoder-decoder based deep learning network for automated spine segmentation.

Scientific reports Apr 16, 2025
Segmenting the spine from CT images is crucial for diagnosing and treating spine-related conditions but remains challenging due to the spine's complex anatomy and imaging artifacts. This study introduces a novel encoder-decoder-based deep learning ap...
Deep Learning Algorithms Humans Image Processing, Computer-Assisted Tomography, X-Ray Computed Neural Networks, Computer Spine
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Deep learning-based automatic segmentation of cerebral infarcts on diffusion MRI.

Scientific reports Apr 16, 2025
We explored effects of (1) training with various sample sizes of multi-site vs. single-site training data, (2) cross-site domain adaptation, and (3) data sources and features on the performance of algorithms segmenting cerebral infarcts on Magnetic R...
Humans Algorithms Image Processing, Computer-Assisted Deep Learning Cerebral Infarction Diffusion Magnetic Resonance Imaging
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A deep learning approach for quantifying CT perfusion parameters in stroke.

Biomedical physics & engineering express Apr 16, 2025
. Computed tomography perfusion (CTP) imaging is widely used for assessing acute ischemic stroke. However, conventional methods for quantifying CTP images, such as singular value decomposition (SVD), often lead to oscillations in the estimated residu...
Perfusion Cerebrovascular Circulation Perfusion Imaging Image Processing, Computer-Assisted Stroke Tomography, X-Ray Computed Male Deep Learning Algorithms Brain Humans
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Deep learning-based acceleration of muscle water T2 mapping in patients with neuromuscular diseases by more than 50% - translating quantitative MRI from research to clinical routine.

PloS one Apr 16, 2025
BACKGROUND: Quantitative muscle water T2 (T2w) mapping is regarded as a biomarker for disease activity and response to treatment in neuromuscular diseases (NMD). However, the implementation in clinical settings is limited due to long scanning times a...
Muscular Dystrophy, Facioscapulohumeral Muscle, Skeletal Neuromuscular Diseases Water Humans Young Adult Female Image Processing, Computer-Assisted Middle Aged Adult Magnetic Resonance Imaging Male Deep Learning
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Using pathology images and artificial intelligence to identify bacterial infections and their types.

Journal of microbiological methods Apr 14, 2025
Bacterial infections pose a significant biosafety concern, making early and accurate diagnosis essential for effective treatment and prognosis. Traditional diagnostic methods, while reliable, are often slow and fail to meet urgent clinical demands. I...
Image Processing, Computer-Assisted Humans Bacteria Artificial Intelligence Bacterial Infections Algorithms
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Utilizing Pix2Pix conditional generative adversarial networks to recover missing data in preclinical PET scanner sinogram gaps.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Apr 14, 2025
BACKGROUND: The presence of a gap between adjacent detector blocks in Positron Emission Tomography (PET) scanners introduces a partial loss of projection data, which can degrade the image quality and quantitative accuracy of reconstructed PET images....
Positron-Emission Tomography Signal-To-Noise Ratio Phantoms, Imaging Generative Adversarial Networks Animals Image Processing, Computer-Assisted Mice Neural Networks, Computer Algorithms
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A hybrid learning network with progressive resizing and PCA for diagnosis of cervical cancer on WSI slides.

Scientific reports Apr 14, 2025
Current artificial intelligence (AI) trends are revolutionizing medical image processing, greatly improving cervical cancer diagnosis. Machine learning (ML) algorithms can discover patterns and anomalies in medical images, whereas deep learning (DL) ...
Algorithms Female Uterine Cervical Neoplasms Neural Networks, Computer Machine Learning Image Interpretation, Computer-Assisted Deep Learning Image Processing, Computer-Assisted Principal Component Analysis Humans
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Accelerated diffusion tensor imaging with self-supervision and fine-tuning.

Scientific reports Apr 14, 2025
Diffusion tensor imaging (DTI) is essential for assessing brain microstructure but requires long acquisition times, limiting clinical use. Recent deep learning (DL) approaches, such as SuperDTI or deepDTI, improve DTI metrics but demand large, high-q...
Humans Brain Connectome Diffusion Tensor Imaging Deep Learning Image Processing, Computer-Assisted
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