Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Medical Image Understanding and Analysis [[electronic resource] ] : 23rd Conference, MIUA 2019, Liverpool, UK, July 24–26, 2019, Proceedings / / edited by Yalin Zheng, Bryan M. Williams, Ke Chen
| Medical Image Understanding and Analysis [[electronic resource] ] : 23rd Conference, MIUA 2019, Liverpool, UK, July 24–26, 2019, Proceedings / / edited by Yalin Zheng, Bryan M. Williams, Ke Chen |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XV, 507 p. 220 illus., 164 illus. in color.) |
| Disciplina | 006.6 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Optical data processing
Machine learning Pattern recognition Bioinformatics Image Processing and Computer Vision Machine Learning Pattern Recognition Computational Biology/Bioinformatics |
| ISBN | 3-030-39343-7 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Oncology and Tumour Imaging -- Lesion, Wound and Ulcer Analysis -- Biostatistics -- Fetal Imaging -- Enhancement and Reconstruction -- Diagnosis, Classication and Treatment -- Vessel and Nerve Analysis -- Image Registration -- Image Segmentation -- Ophthalmic Imaging -- Posters. |
| Record Nr. | UNISA-996465343003316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Medical Image Understanding and Analysis : 23rd Conference, MIUA 2019, Liverpool, UK, July 24–26, 2019, Proceedings / / edited by Yalin Zheng, Bryan M. Williams, Ke Chen
| Medical Image Understanding and Analysis : 23rd Conference, MIUA 2019, Liverpool, UK, July 24–26, 2019, Proceedings / / edited by Yalin Zheng, Bryan M. Williams, Ke Chen |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XV, 507 p. 220 illus., 164 illus. in color.) |
| Disciplina | 006.6 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Optical data processing
Machine learning Pattern recognition Bioinformatics Image Processing and Computer Vision Machine Learning Pattern Recognition Computational Biology/Bioinformatics |
| ISBN | 3-030-39343-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Oncology and Tumour Imaging -- Lesion, Wound and Ulcer Analysis -- Biostatistics -- Fetal Imaging -- Enhancement and Reconstruction -- Diagnosis, Classication and Treatment -- Vessel and Nerve Analysis -- Image Registration -- Image Segmentation -- Ophthalmic Imaging -- Posters. |
| Record Nr. | UNINA-9910373925603321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Ophthalmic Medical Image Analysis [[electronic resource] ] : 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, Proceedings / / edited by Huazhu Fu, Mona K. Garvin, Tom MacGillivray, Yanwu Xu, Yalin Zheng
| Ophthalmic Medical Image Analysis [[electronic resource] ] : 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, Proceedings / / edited by Huazhu Fu, Mona K. Garvin, Tom MacGillivray, Yanwu Xu, Yalin Zheng |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XI, 192 p. 80 illus., 78 illus. in color.) |
| Disciplina | 617.7 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Artificial intelligence Computer science—Mathematics Computer organization Image Processing and Computer Vision Artificial Intelligence Mathematics of Computing Computer Systems Organization and Communication Networks |
| ISBN | 3-030-32956-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Dictionary Learning Informed Deep Neural Network with Application to OCT Images -- Structure-aware Noise Reduction Generative Adversarial Network for Optical Coherence Tomography Image -- Region-Based Segmentation of Capillary Density in Optical Coherence Tomography Angiography -- An amplified-target loss approach for photoreceptor layer segmentation in pathological OCT scans -- Foveal avascular zone segmentation in clinical routine fluorescein angiographies using multitask learning -- Guided M-Net for High-resolution Biomedical Image Segmentation with Weak Boundaries -- 3D-CNN for Glaucoma Detection using Optical Coherence Tomography -- Semi-supervised Adversarial Learning for Diabetic Retinopathy Screening -- Shape Decomposition of Foveal Pit Morphology using Scan Geometry Corrected OCT -- U-Net with spatial pyramid pooling for drusen segmentation in optical coherence tomography -- Deriving Visual Cues from Deep Learning to Achieve Subpixel Cell Segmentation in Adaptive Optics Retinal Images -- Robust Optic Disc Localization by Large Scale Learning -- The Channel Attention based Context Encoder Network for Inner Limiting Membrane Detections -- Fundus Image based Retinal Vessel Segmentation Utilizing A Fast and Accurate Fully Convolutional Network -- Network pruning for OCT image classification -- An improved MPB-CNN segmentation method for edema area and neurosensory retinal detachment in SD-OCT images -- Encoder-Decoder Attention Network for Lesion Segmentation of Diabetic Retinopathy -- Multi-Discriminator Generative Adversarial Networks for improved thin retinal vessel segmentation -- Fovea Localization in Fundus Photographs by Faster R-CNN with Physiological Prior -- Aggressive Posterior Retinopathy of Prematurity Automated Diagnosis via a Deep Convolutional Network -- Automated Stage Analysis of Retinopathy of Prematurity Using Joint Segmentation and Multi-Instance Learning -- Retinopathy Diagnosis using Semi-supervised Multi-channel Generative Adversarial Network. |
| Record Nr. | UNISA-996466320303316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Ophthalmic Medical Image Analysis : 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, Proceedings / / edited by Huazhu Fu, Mona K. Garvin, Tom MacGillivray, Yanwu Xu, Yalin Zheng
| Ophthalmic Medical Image Analysis : 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, Proceedings / / edited by Huazhu Fu, Mona K. Garvin, Tom MacGillivray, Yanwu Xu, Yalin Zheng |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XI, 192 p. 80 illus., 78 illus. in color.) |
| Disciplina |
617.7
616.07 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Artificial intelligence Computer science—Mathematics Computer organization Image Processing and Computer Vision Artificial Intelligence Mathematics of Computing Computer Systems Organization and Communication Networks |
| ISBN | 3-030-32956-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Dictionary Learning Informed Deep Neural Network with Application to OCT Images -- Structure-aware Noise Reduction Generative Adversarial Network for Optical Coherence Tomography Image -- Region-Based Segmentation of Capillary Density in Optical Coherence Tomography Angiography -- An amplified-target loss approach for photoreceptor layer segmentation in pathological OCT scans -- Foveal avascular zone segmentation in clinical routine fluorescein angiographies using multitask learning -- Guided M-Net for High-resolution Biomedical Image Segmentation with Weak Boundaries -- 3D-CNN for Glaucoma Detection using Optical Coherence Tomography -- Semi-supervised Adversarial Learning for Diabetic Retinopathy Screening -- Shape Decomposition of Foveal Pit Morphology using Scan Geometry Corrected OCT -- U-Net with spatial pyramid pooling for drusen segmentation in optical coherence tomography -- Deriving Visual Cues from Deep Learning to Achieve Subpixel Cell Segmentation in Adaptive Optics Retinal Images -- Robust Optic Disc Localization by Large Scale Learning -- The Channel Attention based Context Encoder Network for Inner Limiting Membrane Detections -- Fundus Image based Retinal Vessel Segmentation Utilizing A Fast and Accurate Fully Convolutional Network -- Network pruning for OCT image classification -- An improved MPB-CNN segmentation method for edema area and neurosensory retinal detachment in SD-OCT images -- Encoder-Decoder Attention Network for Lesion Segmentation of Diabetic Retinopathy -- Multi-Discriminator Generative Adversarial Networks for improved thin retinal vessel segmentation -- Fovea Localization in Fundus Photographs by Faster R-CNN with Physiological Prior -- Aggressive Posterior Retinopathy of Prematurity Automated Diagnosis via a Deep Convolutional Network -- Automated Stage Analysis of Retinopathy of Prematurity Using Joint Segmentation and Multi-Instance Learning -- Retinopathy Diagnosis using Semi-supervised Multi-channel Generative Adversarial Network. |
| Record Nr. | UNINA-9910349273003321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||