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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 |
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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Intelligent Biosignal Analysis Methods
| Intelligent Biosignal Analysis Methods |
| Autore | Jović Alan |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (256 p.) |
| Soggetto topico | Information technology industries |
| Soggetto non controllato |
accelerometer
accuracy Alzheimer's disease autonomic nervous system brain functional connectivity classifiers CNN convolution neural network (CNN) covariate shift cross-participant DEAP deep learning disgust drowsiness classification drowsiness detection EEG EEG features electrocardiogram electrocardiography electroencephalogram (EEG) electroencephalography (EEG) emotion emotion recognition emotional state event-centered data segmentation eye blinks rate fall detection fatigue detection feature extraction feature selection frequency band fusion galvanic skin response heart rate individual differences inter-participant inter-subject variability k-fold validation machine learning mental workload Mish myocardial infarction n/a neural network-based refinement non-local attention mechanism non-stationarity olfactory training optimal shrinkage phase-locked value (PLV) photoplethysmography (PPG) psychophysics residual attention residual network sensitivity signal quality index skin conductance level sleep stage scoring sleep staging smell spatial transformer networks stress surgery image T-end annotation tSQI wearable device wearable sensors window duration wine sensory analysis |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557354803321 |
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Jović Alan
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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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