國立高雄大學圖資館 |

Language: English

Back

Ophthalmic Medical Image Analysis8th...

(1998 :)

Ophthalmic Medical Image Analysis8th International Workshop, OMIA 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Ophthalmic Medical Image Analysisedited by Huazhu Fu ... [et al.].
Reminder of title:	8th International Workshop, OMIA 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /
remainder title:	OMIA 2021
other author:	Fu, Huazhu.
corporate name:
Published:	Cham :Springer International Publishing :2021.
Description:	ix, 200 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	PathologyCongresses.Data processing
Online resource:	https://doi.org/10.1007/978-3-030-87000-3
ISBN:	9783030870003$q(electronic bk.)

Ophthalmic Medical Image Analysis8th International Workshop, OMIA 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /
Ophthalmic Medical Image Analysis8th International Workshop, OMIA 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /[electronic resource] :OMIA 2021edited by Huazhu Fu ... [et al.]. - Cham :Springer International Publishing :2021. - ix, 200 p. :ill., digital ;24 cm. - Lecture notes in computer science,129700302-9743 ;. - Lecture notes in computer science ;4891..

Adjacent Scale Fusion and Corneal Position Embedding for Corneal Ulcer Segmentation -- Longitudinal detection of diabetic retinopathy early severity grade changes using deep learning -- Intra-operative OCT (iOCT) Image Quality Enhancement: A Super-Resolution Approach using High Quality iOCT 3D Scans -- Diabetic Retinopathy Detection based on Weakly Supervised Object Localization and Knowledge Driven Attribute Mining -- FARGO: A Joint Framework for FAZ and RV Segmentation from OCTA Images -- CDLRS: Collaborative Deep Learning Model with Joint Regression and Segmentation for Automatic Fovea Localization -- U-Net with Hierarchical Bottleneck Attention for Landmark Detection in Fundus Images of the Degenerated Retina -- Radial U-Net: Improving DMEK Graft Detachment Segmentation in Radial AS-OCT Scans -- Guided Adversarial Adaptation Network for Retinal and Choroidal Layer Segmentation -- Juvenile Refractive Power Prediction based on Corneal Curvature and Axial Length via a Domain Knowledge Embedding Network -- Peripapillary Atrophy Segmentation with Boundary Guidance -- Are cardiovascular risk scores from genome and retinal image complementary? A deep learning investigation in a diabetic cohort -- Dual-branch Attention Network and Atrous Spatial Pyramid Pooling for Diabetic Retinopathy Classification Using Ultra-Widefield Images -- Self-Adaptive Transfer Learning for Multicenter Glaucoma Classification in Fundus Retina Images -- Multi-Modality Images Analysis: A Baseline for Glaucoma Grading via Deep Learning -- Impact of data augmentation on retinal OCT image segmentation for diabetic macular edema analysis -- Representation and Reconstruction of Image-Based Structural Patterns of Glaucomatous Defects Using Only Two Latent Variables from a Variational Autoencoder -- Stacking Ensemble Learning in Deep Domain Adaptation for Ophthalmic Image Classification -- Attention Guided Slit Lamp Image Quality Assessment -- Robust Retinal Vessel Segmentation from a Data Augmentation Perspective.

This book constitutes the refereed proceedings of the 8th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2021, held in conjunction with the 24th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2021, in Strasbourg, France, in September 2021.* The 20 papers presented at OMIA 2021 were carefully reviewed and selected from 31 submissions. The papers cover various topics in the field of ophthalmic medical image analysis and challenges in terms of reliability and validation, number and type of conditions considered, multi-modal analysis (e.g., fundus, optical coherence tomography, scanning laser ophthalmoscopy), novel imaging technologies, and the effective transfer of advanced computer vision and machine learning technologies. *The workshop was held virtually.

ISBN: 9783030870003$q(electronic bk.)

Standard No.: 10.1007/978-3-030-87000-3doiSubjects--Topical Terms:

823085
Pathology
--Data processing--Congresses.

LC Class. No.: RB38 / .O64 2021

Dewey Class. No.: 616.07

Ophthalmic Medical Image Analysis8th International Workshop, OMIA 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /
LDR:04166nmm a2200385 a 4500 001 609379
003 DE-He213
005 20210918092348.0
006 m d
007 cr nn 008maaau
008 220222s2021 sz s 0 eng d
020 $a 9783030870003$q(electronic bk.)
020 $a 9783030869991$q(paper)
024 7 $a 10.1007/978-3-030-87000-3 $2 doi
035 $a 978-3-030-87000-3
040 $a GP $c GP
041 0 $a eng
050 4 $a RB38 $b .O64 2021
072 7 $a UYT $2 bicssc
072 7 $a COM012000 $2 bisacsh
072 7 $a UYT $2 thema
072 7 $a UYQV $2 thema
082 0 4 $a 616.07 $2 23
090 $a RB38 $b .O55 2021
111 2 $n (3rd : $d 1998 : $c Amsterdam, Netherlands) $3 194767
245 1 0 $a Ophthalmic Medical Image Analysis $h [electronic resource] : $b 8th International Workshop, OMIA 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings / $c edited by Huazhu Fu ... [et al.].
246 3 $a OMIA 2021
246 3 $a MICCAI 2021
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a ix, 200 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 0302-9743 ; $v 12970
490 1 $a Image processing, computer vision, pattern recognition, and graphics
505 0 $a Adjacent Scale Fusion and Corneal Position Embedding for Corneal Ulcer Segmentation -- Longitudinal detection of diabetic retinopathy early severity grade changes using deep learning -- Intra-operative OCT (iOCT) Image Quality Enhancement: A Super-Resolution Approach using High Quality iOCT 3D Scans -- Diabetic Retinopathy Detection based on Weakly Supervised Object Localization and Knowledge Driven Attribute Mining -- FARGO: A Joint Framework for FAZ and RV Segmentation from OCTA Images -- CDLRS: Collaborative Deep Learning Model with Joint Regression and Segmentation for Automatic Fovea Localization -- U-Net with Hierarchical Bottleneck Attention for Landmark Detection in Fundus Images of the Degenerated Retina -- Radial U-Net: Improving DMEK Graft Detachment Segmentation in Radial AS-OCT Scans -- Guided Adversarial Adaptation Network for Retinal and Choroidal Layer Segmentation -- Juvenile Refractive Power Prediction based on Corneal Curvature and Axial Length via a Domain Knowledge Embedding Network -- Peripapillary Atrophy Segmentation with Boundary Guidance -- Are cardiovascular risk scores from genome and retinal image complementary? A deep learning investigation in a diabetic cohort -- Dual-branch Attention Network and Atrous Spatial Pyramid Pooling for Diabetic Retinopathy Classification Using Ultra-Widefield Images -- Self-Adaptive Transfer Learning for Multicenter Glaucoma Classification in Fundus Retina Images -- Multi-Modality Images Analysis: A Baseline for Glaucoma Grading via Deep Learning -- Impact of data augmentation on retinal OCT image segmentation for diabetic macular edema analysis -- Representation and Reconstruction of Image-Based Structural Patterns of Glaucomatous Defects Using Only Two Latent Variables from a Variational Autoencoder -- Stacking Ensemble Learning in Deep Domain Adaptation for Ophthalmic Image Classification -- Attention Guided Slit Lamp Image Quality Assessment -- Robust Retinal Vessel Segmentation from a Data Augmentation Perspective.
520 $a This book constitutes the refereed proceedings of the 8th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2021, held in conjunction with the 24th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2021, in Strasbourg, France, in September 2021.* The 20 papers presented at OMIA 2021 were carefully reviewed and selected from 31 submissions. The papers cover various topics in the field of ophthalmic medical image analysis and challenges in terms of reliability and validation, number and type of conditions considered, multi-modal analysis (e.g., fundus, optical coherence tomography, scanning laser ophthalmoscopy), novel imaging technologies, and the effective transfer of advanced computer vision and machine learning technologies. *The workshop was held virtually.
650 0 $a Pathology $x Data processing $v Congresses. $3 823085
650 0 $a Eye $x Imaging $v Congresses. $3 823086
650 1 4 $a Image Processing and Computer Vision. $3 274051
650 2 4 $a Artificial Intelligence. $3 212515
650 2 4 $a Pattern Recognition. $3 273706
650 2 4 $a Computer Systems Organization and Communication Networks. $3 273709
700 1 $a Fu, Huazhu. $3 853551
710 2 $a SpringerLink (Online service) $3 273601
711 2 $n (3rd : $d 1998 : $c Amsterdam, Netherlands) $3 194767
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in computer science ; $v 4891. $3 383229
830 0 $a Image processing, computer vision, pattern recognition, and graphics. $3 823073
856 4 0 $u https://doi.org/10.1007/978-3-030-87000-3
950 $a Computer Science (SpringerNature-11645)