AIMC Topic: Image Processing, Computer-Assisted

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Diabetic retinopathy detection using adaptive deep convolutional neural networks on fundus images.

Scientific reports Jul 9, 2025
Diabetic retinopathy (DR) is an age-related macular degeneration eye disease problem that causes pathological changes in the retinal neural and vascular system. Recently, fundus imaging is a popular technology and widely used for clinical diagnosis, ...
Image Interpretation, Computer-Assisted Deep Learning Convolutional Neural Networks Fundus Oculi Retina Image Processing, Computer-Assisted Neural Networks, Computer Algorithms Humans Diabetic Retinopathy
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Deep learning-based automatic detection and grading of disk herniation in lumbar magnetic resonance images.

Scientific reports Jul 9, 2025
Magnetic resonance imaging of the lumbar spine is a key technique for clarifying the cause of disease. The greatest challenges today are the repetitive and time-consuming process of interpreting these complex MR images and the problem of unequal diag...
Female Adult Male Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Lumbar Vertebrae Middle Aged Deep Learning Image Interpretation, Computer-Assisted Intervertebral Disc Displacement
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A hybrid deep learning model EfficientNet with GRU for breast cancer detection from histopathology images.

Scientific reports Jul 9, 2025
Breast cancer remains a significant global health challenge among women, with histopathological image analysis playing a critical role in early detection. However, existing diagnostic models often struggle to extract complex patterns from high-resolu...
Breast Neoplasms Deep Learning Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Convolutional Neural Networks Humans Algorithms Female
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Limited-angle SPECT image reconstruction using deep image prior.

Physics in medicine and biology Jul 9, 2025
. In single-photon emission computed tomography (SPECT) image reconstruction, limited-angle conditions lead to a loss of frequency components, which distort the reconstructed tomographic image along directions corresponding to the non-collected proje...
Humans Image Processing, Computer-Assisted Phantoms, Imaging Tomography, Emission-Computed, Single-Photon Signal-To-Noise Ratio
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MANet: multi-attention network for polyp segmentation.

Medical engineering & physics Jul 8, 2025
Currently, colonoscopy stands as the most efficient approach for detecting colorectal polyps. In clinical diagnosis, colorectal cancer is closely related to colorectal polyps. Therefore, precise segmentation of polyps holds paramount importance for t...
Colonoscopy Image Processing, Computer-Assisted Colonic Polyps Humans Neural Networks, Computer
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Comparison of 2D, 2.5D, and 3D segmentation networks for mandibular canals in CBCT images: a study on public and external datasets.

BMC oral health Jul 8, 2025
The purpose of this study was to compare the performances of 2D, 2.5D, and 3D CNN-based segmentation networks, along with a 3D vision transformer-based segmentation network, for segmenting mandibular canals (MCs) on the public and external CBCT datas...
Mandible Cone-Beam Computed Tomography Humans Imaging, Three-Dimensional Neural Networks, Computer Image Processing, Computer-Assisted
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Explainable deep learning approaches for high precision early melanoma detection using dermoscopic images.

Scientific reports Jul 8, 2025
Detecting skin melanoma in the early stage using dermoscopic images presents a complex challenge due to the inherent variability in images. Utilizing dermatology datasets, the study aimed to develop Automated Diagnostic Systems for early skin cancer ...
Deep Learning Melanoma Image Processing, Computer-Assisted Skin Neoplasms Humans Early Detection of Cancer Dermoscopy Image Interpretation, Computer-Assisted Reproducibility of Results
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Robust Bi-CBMSegNet framework for advancing breast mass segmentation in mammography with a dual module encoder-decoder approach.

Scientific reports Jul 8, 2025
Breast cancer is a prevalent disease affecting millions of women worldwide, and early screening can significantly reduce mortality rates. Mammograms are widely used for screening, but manual readings can lead to misdiagnosis. Computer-assisted diagno...
Breast Mammography Radiographic Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Algorithms Early Detection of Cancer Female Breast Neoplasms Humans
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Integrating radiomic texture analysis and deep learning for automated myocardial infarction detection in cine-MRI.

Scientific reports Jul 8, 2025
Robust differentiation between infarcted and normal myocardial tissue is essential for improving diagnostic accuracy and personalizing treatment in myocardial infarction (MI). This study proposes a hybrid framework combining radiomic texture analysis...
Humans Male Deep Learning Radiomics Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Myocardial Infarction Magnetic Resonance Imaging, Cine
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Lossy DICOM conversion may affect AI performance.

Scientific reports Jul 8, 2025
Many pathologies have started to digitize their glass slides. To ensure long term accessibility, it is desirable to store them in the DICOM format. Currently, many scanners initially store the images in vendor-specific formats and only provide DICOM ...
Neural Networks, Computer Artificial Intelligence Male Image Processing, Computer-Assisted Female Humans
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