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Biomedical image registration, domain generalisation and out-of-distribution analysis : MICCAI 2021 Challenges, MIDOG 2021, MOOD 2021, and Learn2Reg 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27-October 1, 2021, proceedings / / Marc Aubreville, David Zimmerer, Mattias P. Heinrich, editors
| Biomedical image registration, domain generalisation and out-of-distribution analysis : MICCAI 2021 Challenges, MIDOG 2021, MOOD 2021, and Learn2Reg 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27-October 1, 2021, proceedings / / Marc Aubreville, David Zimmerer, Mattias P. Heinrich, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (201 pages) |
| Disciplina | 616.07540285 |
| Collana | Lecture notes in computer science |
| Soggetto topico | Diagnostic imaging - Data processing |
| ISBN | 3-030-97281-X |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996464536003316 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Biomedical image registration, domain generalisation and out-of-distribution analysis : MICCAI 2021 Challenges, MIDOG 2021, MOOD 2021, and Learn2Reg 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27-October 1, 2021, proceedings / / Marc Aubreville, David Zimmerer, Mattias P. Heinrich, editors
| Biomedical image registration, domain generalisation and out-of-distribution analysis : MICCAI 2021 Challenges, MIDOG 2021, MOOD 2021, and Learn2Reg 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27-October 1, 2021, proceedings / / Marc Aubreville, David Zimmerer, Mattias P. Heinrich, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (201 pages) |
| Disciplina | 616.07540285 |
| Collana | Lecture notes in computer science |
| Soggetto topico | Diagnostic imaging - Data processing |
| ISBN | 3-030-97281-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910551826103321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Mitosis Domain Generalization and Diabetic Retinopathy Analysis [[electronic resource] ] : MICCAI Challenges MIDOG 2022 and DRAC 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18–22, 2022, Proceedings / / edited by Bin Sheng, Marc Aubreville
| Mitosis Domain Generalization and Diabetic Retinopathy Analysis [[electronic resource] ] : MICCAI Challenges MIDOG 2022 and DRAC 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18–22, 2022, Proceedings / / edited by Bin Sheng, Marc Aubreville |
| Autore | Sheng Bin |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (250 pages) |
| Disciplina | 006 |
| Altri autori (Persone) | AubrevilleMarc |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing—Digital techniques
Computer vision Computers Application software Machine learning Computer Imaging, Vision, Pattern Recognition and Graphics Computing Milieux Computer and Information Systems Applications Machine Learning |
| Soggetto non controllato |
Ophthalmology
Medical |
| ISBN | 3-031-33658-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface DRAC 2022 -- nnU-Net Pre- and Postprocessing Strategies for UW-OCTA Segmentation Tasks in Diabetic Retinopathy Analysis -- Automated analysis of diabetic retinopathy using vessel segmentation maps as inductive bias -- Bag of Tricks for Diabetic Retinopathy Grading of Ultra-wide Optical Coherence Tomography Angiography Images -- Deep convolutional neural network for image quality assessment and diabetic retinopathy grading -- Diabetic Retinal Overlap Lesion Segmentation Network -- An Ensemble Method to Automatically Grade Diabetic Retinopathy with Optical Coherence Tomography Angiography Images -- Bag of Tricks for Developing Diabetic Retinopathy Analysis Framework to Overcome Data Scarcity -- Deep-OCTA: Ensemble Deep Learning Approaches for Diabetic Retinopathy Analysis on OCTA Images -- Deep Learning-based Multi-tasking System for Diabetic Retinopathy in UW-OCTA images -- Semi-Supervised Semantic Segmentation Methods for UW-OCTA Diabetic Retinopathy Grade Assessment -- Image Quality Assessment based on Multi-Model Ensemble Class-Imbalance Repair Algorithm for Diabetic Retinopathy UW-OCTA Images -- An improved U-Net for diabetic retinopathy segmentation -- A Vision transformer based deep learning architecture for automatic diagnosis of diabetic retinopathy in optical coherence tomography angiography -- Segmentation, Classification, and Quality Assessment of UW-OCTA Images for the Diagnosis of Diabetic Retinopathy -- Data Augmentation by Fourier Transformation for Class-Imbalance : Application to Medical Image Quality Assessment -- Automatic image quality assessment and DR grading method based on convolutional neural network -- A transfer learning based model ensemble method for image quality assessment and diabetic retinopathy grading -- Automatic Diabetic Retinopathy Lesion Segmentation in UW-OCTA Images using Transfer Learning -- Preface MIDOG 2022 -- Reference Algorithms for the Mitosis Domain Generalization (MIDOG) 2022 Challenge -- Radial Prediction Domain Adaption Classifier for the MIDOG 2022 challenge -- Detecting Mitoses with a Convolutional Neural Network for MIDOG 2022 Challenge -- Tackling Mitosis Domain Generalization in Histopathology Images with Color Normalization -- "A Deep Learning based Ensemble Model for Generalized Mitosis Detection in H&E stained Whole Slide Images" -- Fine-Grained Hard-Negative Mining: Generalizing Mitosis Detection with a Fifth of the MIDOG 2022 Dataset -- Multi-task RetinaNet for mitosis detection. . |
| Record Nr. | UNINA-9910728397403321 |
Sheng Bin
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Mitosis Domain Generalization and Diabetic Retinopathy Analysis [[electronic resource] ] : MICCAI Challenges MIDOG 2022 and DRAC 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18–22, 2022, Proceedings / / edited by Bin Sheng, Marc Aubreville
| Mitosis Domain Generalization and Diabetic Retinopathy Analysis [[electronic resource] ] : MICCAI Challenges MIDOG 2022 and DRAC 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18–22, 2022, Proceedings / / edited by Bin Sheng, Marc Aubreville |
| Autore | Sheng Bin |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (250 pages) |
| Disciplina | 006 |
| Altri autori (Persone) | AubrevilleMarc |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing—Digital techniques
Computer vision Computers Application software Machine learning Computer Imaging, Vision, Pattern Recognition and Graphics Computing Milieux Computer and Information Systems Applications Machine Learning |
| Soggetto non controllato |
Ophthalmology
Medical |
| ISBN | 3-031-33658-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface DRAC 2022 -- nnU-Net Pre- and Postprocessing Strategies for UW-OCTA Segmentation Tasks in Diabetic Retinopathy Analysis -- Automated analysis of diabetic retinopathy using vessel segmentation maps as inductive bias -- Bag of Tricks for Diabetic Retinopathy Grading of Ultra-wide Optical Coherence Tomography Angiography Images -- Deep convolutional neural network for image quality assessment and diabetic retinopathy grading -- Diabetic Retinal Overlap Lesion Segmentation Network -- An Ensemble Method to Automatically Grade Diabetic Retinopathy with Optical Coherence Tomography Angiography Images -- Bag of Tricks for Developing Diabetic Retinopathy Analysis Framework to Overcome Data Scarcity -- Deep-OCTA: Ensemble Deep Learning Approaches for Diabetic Retinopathy Analysis on OCTA Images -- Deep Learning-based Multi-tasking System for Diabetic Retinopathy in UW-OCTA images -- Semi-Supervised Semantic Segmentation Methods for UW-OCTA Diabetic Retinopathy Grade Assessment -- Image Quality Assessment based on Multi-Model Ensemble Class-Imbalance Repair Algorithm for Diabetic Retinopathy UW-OCTA Images -- An improved U-Net for diabetic retinopathy segmentation -- A Vision transformer based deep learning architecture for automatic diagnosis of diabetic retinopathy in optical coherence tomography angiography -- Segmentation, Classification, and Quality Assessment of UW-OCTA Images for the Diagnosis of Diabetic Retinopathy -- Data Augmentation by Fourier Transformation for Class-Imbalance : Application to Medical Image Quality Assessment -- Automatic image quality assessment and DR grading method based on convolutional neural network -- A transfer learning based model ensemble method for image quality assessment and diabetic retinopathy grading -- Automatic Diabetic Retinopathy Lesion Segmentation in UW-OCTA Images using Transfer Learning -- Preface MIDOG 2022 -- Reference Algorithms for the Mitosis Domain Generalization (MIDOG) 2022 Challenge -- Radial Prediction Domain Adaption Classifier for the MIDOG 2022 challenge -- Detecting Mitoses with a Convolutional Neural Network for MIDOG 2022 Challenge -- Tackling Mitosis Domain Generalization in Histopathology Images with Color Normalization -- "A Deep Learning based Ensemble Model for Generalized Mitosis Detection in H&E stained Whole Slide Images" -- Fine-Grained Hard-Negative Mining: Generalizing Mitosis Detection with a Fifth of the MIDOG 2022 Dataset -- Multi-task RetinaNet for mitosis detection. . |
| Record Nr. | UNISA-996534463903316 |
|
Sheng Bin
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||