VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021.
Carole H. SudreKimberlin M. H. van WijnenFlorian DubostHieab AdamsDavid AtkinsonFrederik BarkhofMahlet A. BirhanuEsther E. BronRobin CamarasaNish ChaturvediYuan ChenZihao ChenShuai ChenQi DouTavia E. EvansIvan EzhovHaojun GaoMarta Gironés-SangüesaJuan Domingo GispertBeatriz Gomez AnsonAlun D. HughesMohammad Arfan IkramSilvia IngalaHans Rolf JägerFlorian KoflerHugo J. KuijfDenis KutnarMinho LeeBo LiLuigi LorenziniBjoern H. MenzeJosé Luis MolinuevoYiwei PanÉlodie PuybareauRafael RehwaldRuisheng SuPengcheng ShiLorna SmithTherese TillinGuillaume TochonHélène UrienBas H. M. van der VeldenIsabelle F. van der VelpenBenedikt WiestlerFrank J. WoltersPinar YilmazMarius de GrootMeike W. VernooijMarleen de BruijnePublished in: Medical Image Anal. (2024)
Keyphrases
- lesion segmentation
- fundus images
- diabetic retinopathy
- vessel segmentation
- blood vessels
- tubular structures
- retinal images
- digital mammograms
- optic disc
- dermoscopy images
- grand challenge
- multiscale
- automatic detection
- lesion detection
- image segmentation
- image analysis
- level set
- segmentation algorithm
- medical images
- optical coherence tomography
- detection algorithm
- segmentation method
- international workshop
- angiography images
- computer aided detection
- reliable detection
- computer aided diagnosis
- region growing
- bounding box
- computer aided
- breast mri
- video sequences
- multiple sclerosis lesions
- retinal fundus images
- automated analysis
- medical imaging
- multiple sclerosis
- blood flow