Artificial Intelligence in Medical Image Processing and Segmentation

• Pubblicazione: MDPI - Multidisciplinary Digital Publishing Institute, 2023
• Descrizione fisica: 1 online resource (348 p.)
• Soggetto topico: History of engineering & technology; Technology: general issues
• Soggetto non controllato: 2D ultrasound image; 2D/3D registration; 3D virtual reconstruction; ALO; artificial hummingbird algorithm; artificial intelligence; artificial neural network (ANN); attention mechanism; auto-segmentation; automatic volume measurement; breast cancer; breast density; CAD; canonical correlation analysis (CCA); carbon ion radiotherapy; CBCT; cervical cancer; cervical net; children; CNN; comparison; computer vision applications; convolutional neural network; Convolutional Neural Networks; Cranio-Maxillofacial surgery; CT; DarkNet-19; deep learning; deep learning structures; DICOM; directional total variation; disease discrimination accuracy; dual-energy CT; edge computing; ensemble learning; feature fusion; feature selection; fundus image; GAN; Grad-CAM; hematoxylin eosin; histopathological; histopathology; histopathology images; image enhancement; image inpainting; image normalization; image preprocessing; image registration; image segmentation; image-guided radiotherapy; in-house; instance segmentation; k-nearest neighbour (KNN); lesion segmentation; limited-angular range; loss function; magnetic resonance imaging; mandible; mask-transformer-based networks; medical image analysis; medical imaging; mitotic nuclei classification; MobileNet; mp-MRI; MRI; MRI guidance; MRI-only; multi-contrast MRI; NasNet; neuroimaging; nuclei detection; nuclei segmentation; OCT; orthogonal X-ray; osteoarthritis; ovarian tumor; PA; panoptic segmentation; panoramic radiographs; pap smear; particle therapy; patch size; PCA; PCNSL; performance comparisons; prostate cancer; prostate segmentation; pyramidal network; radiomics; random forest (RF); rare neurodevelopmental disorder; rare tumor; ResNet-101; safranin O fast green; scale-adaptive; segmentation; semantic segmentation; shuffle net; ShuffleNet; software; support vector machine; support vector machine (SVM); synthetic CT; teeth segmentation; textural; tooth disease recognition; tuberous sclerosis complex; two-step method; U-Net; ultrasound bladder scanner; urinary disease
• Sommario/riassunto: 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.
• Titolo autorizzato: Artificial Intelligence in Medical Image Processing and Segmentation
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910743276403321
• Lo trovi qui: Univ. Federico II