Artificial Intelligence in Medical Image Processing and Segmentation

This reprint showcases a selection of bleeding-edge articles about medical image processing and segmentation workflows based on artificial intelligence algorithms. The proposed papers are applied to multiple and different anatomical districts and clinical scenarios.

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Médium:	Online
Jazyk:	angličtina
Vydáno:	MDPI - Multidisciplinary Digital Publishing Institute 2023
Témata:	fundus image image registration deep learning computer vision applications nuclei segmentation histopathology Grad-CAM semantic segmentation instance segmentation nuclei detection pap smear cervical net shuffle net canonical correlation analysis (CCA) support vector machine (SVM) random forest (RF) k-nearest neighbour (KNN) artificial neural network (ANN) dual-energy CT two-step method limited-angular range directional total variation PA CNN tooth disease recognition image segmentation image preprocessing breast cancer mitotic nuclei classification histopathology images artificial hummingbird algorithm medical imaging cervical cancer feature fusion feature selection deep learning structures support vector machine disease discrimination accuracy performance comparisons 2D/3D registration orthogonal X-ray breast density CAD image enhancement textural auto-segmentation neuroimaging magnetic resonance imaging ovarian tumor 2D ultrasound image image inpainting lesion segmentation attention mechanism GAN medical image analysis synthetic CT MRI guidance MRI-only image-guided radiotherapy carbon ion radiotherapy particle therapy rare tumor PCNSL radiomics image normalization MRI prostate cancer prostate segmentation U-Net mp-MRI loss function automatic volume measurement ultrasound bladder scanner edge computing urinary disease artificial intelligence mandible segmentation 3D virtual reconstruction CBCT CT Convolutional Neural Networks comparison in-house software patch size Cranio-Maxillofacial surgery DICOM osteoarthritis histopathological hematoxylin eosin safranin O fast green DarkNet-19 MobileNet NasNet ResNet-101 ShuffleNet PCA ALO ensemble learning OCT pyramidal network scale-adaptive teeth segmentation panoramic radiographs mask-transformer-based networks panoptic segmentation tuberous sclerosis complex children convolutional neural network multi-contrast MRI rare neurodevelopmental disorder thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
On-line přístup:	ONIX_20230911_9783036585871_126
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Shrnutí:	This reprint showcases a selection of bleeding-edge articles about medical image processing and segmentation workflows based on artificial intelligence algorithms. The proposed papers are applied to multiple and different anatomical districts and clinical scenarios.

Artificial Intelligence in Medical Image Processing and Segmentation

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