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Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Virtual Event, September 27, 2021, Revised Selected Papers, Part I / / edited by Alessandro Crimi, Spyridon Bakas
| Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Virtual Event, September 27, 2021, Revised Selected Papers, Part I / / edited by Alessandro Crimi, Spyridon Bakas |
| Autore | Crimi Alessandro |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2022 |
| Descrizione fisica | 1 online resource (XXI, 489 p. 171 illus., 134 illus. in color.) |
| Disciplina | 006.37 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Computer vision
Artificial intelligence Computer engineering Computer networks Application software Computer Vision Artificial Intelligence Computer Engineering and Networks Computer and Information Systems Applications |
| Soggetto non controllato |
artificial intelligence
bioinformatics computer science computer systems computer vision education image analysis image processing image segmentation learning machine learning medical images neural networks pattern recognition segmentation methods software design software engineering software quality validation verification and validation |
| ISBN | 3-031-08999-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Supervoxel Merging towards Brain Tumor Segmentation -- Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRI -- Modeling multi-annotator uncertainty as multi-class segmentation problem -- Modeling multi-annotator uncertainty as multi-class segmentation problem -- Adaptive unsupervised learning with enhanced feature representation for intra-tumor partitioning and survival prediction for glioblastoma -- Predicting isocitrate dehydrogenase mutation status in glioma using structural brain networks and graph neural networks -- Optimization of Deep Learning based Brain Extraction in MRI for Low Resource Environments. Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task -- Unet3D with Multiple Atrous Convolutions Attention Block for Brain Tumor Segmentation -- BRATS2021: exploring each sequence in multi-modal input for baseline U-net performance -- Automatic Brain Tumor Segmentation using Multi-scale Features and Attention Mechanism -- Simple and Fast Convolutional Neural Network applied to median cross sections for predicting the presence of MGMT promoter methylation in FLAIR MRI scans -- MSViT: Multi Scale Vision Transformer forBiomedical Image Segmentation -- Unsupervised Multimodal -- HarDNet-BTS: A Harmonic Shortcut Network for Brain Tumor Segmentation -- Multimodal Brain Tumor Segmentation Algorithm -- Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images -- Multi-plane UNet++ Ensemble for Glioblastoma Segmentation -- Multimodal Brain Tumor Segmentation using Modified UNet Architecture -- A video data based transfer learning approach for classification of MGMT status in brain tumor MR images -- Multimodal Brain Tumor Segmentation Using a 3D ResUNet in BraTS 2021 -- 3D MRI brain tumour segmentation with autoencoder regularization and Hausdorff distance loss function -- 3D CMM-Net with Deeper Encoder for Semantic Segmentation of Brain Tumors in BraTS2021 Challenge -- Cascaded training pipeline for 3D brain tumor segmentation -- nnU-Net with Region-based Training and Loss Ensembles for Brain Tumor Segmentation -- Brain Tumor Segmentation Using Attention Activated U-Net with Positive Mining -- Automatic segmentation of brain tumor using 3D convolutional neural networks -- Hierarchical and Global Modality Interaction for Brain Tumor Segmentation -- Ensemble Outperforms Single Models in Brain Tumor Segmentation -- Brain Tumor Segmentation using UNet-Context Encoding Network -- Ensemble CNN Networks for GBM Tumors Segmentation using Multi-parametric MRI. |
| Record Nr. | UNISA-996483157303316 |
Crimi Alessandro
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| Cham, : Springer Nature, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Deep Learning in Medical Image Analysis
| Deep Learning in Medical Image Analysis |
| Autore | Zhang Yudong |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (458 p.) |
| Soggetto non controllato |
1D-convolutional neural network
3D segmentation active surface ARMD artificial intelligence autism bayesian inference black box brain tumor breast cancer cancer cancer prediction cervical cancer change detection classifiers colon cancer computation computed tomography (CT) computer vision computers in medicine convolutional neural network convolutional neural networks COVID-19 CycleGAN data augmentation deep learning deep learning classification dermoscopic images diagnosis diagnostics digital pathology discriminant analysis domain adaptation domain transfer ECG signal detection egocentric camera explainability explainable AI fMRI gibbs sampling glcm matrix HER2 image classification image processing image reconstruction imaging infection detection interpretable/explainable machine learning low-dose lung cancer lung disease detection machine learning machine learning models macroscopic images magnetic resonance imaging (MRI) MCMC medical image analysis medical image segmentation medical images medical imaging melanoma meta-learning microwave breast imaging MRI multimodal learning multiple instance learning musculoskeletal images n/a neo-adjuvant treatment object detection open surgery optimizers PET imaging portable monitoring devices quantitative comparison segmentation shifted-scaled dirichlet distribution skin lesion segmentation sparse-angle surgical tools taxonomy texture analysis transfer learning tumor detection tumour cellularity U-Net unsupervised learning white box whole slide image processing X-ray images XAI |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557435103321 |
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Zhang Yudong
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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