Command Palette
Search for a command to run...
Medical Image Segmentation
Medical image segmentation is a task in the field of computer vision aimed at dividing medical images into multiple regions, each representing different objects of interest or structures within the image. The goal is to provide precise and accurate representations of these objects, primarily for diagnosis, treatment planning, and quantitative analysis.
Kvasir-SEG
SSFormer-L
CVC-ClinicDB
DUCK-Net
ETIS-LARIBPOLYPDB
DUCK-Net
Synapse multi-organ CT
Interactive AI-SAM gt box
CVC-ColonDB
RAPUNet
Automatic Cardiac Diagnosis Challenge (ACDC)
FCT
MoNuSeg
Stardist
GlaS
Hi-gMISnet
2018 Data Science Bowl
DoubleUNet
BKAI-IGH NeoPolyp-Small
QTSeg
MICCAI 2015 Multi-Atlas Abdomen Labeling Challenge
MERIT
ACDC
FCT
Medical Segmentation Decathlon
Swin UNETR
CVC-VideoClinicDB
ResUNet++ + TTA
DRIVE
ISIC 2018
ProMISe
Brain US
MedT
CHASE_DB1
EM
UNet++
ISBI 2012 EM Segmentation
CE-Net
RITE
KiU-Net
Kvasir-Instrument
DoubleUNet
ISIC2018
EMCAD
ISIC 2018
EMCAD
Medico automatic polyp segmentation challenge (dataset)
KvasirCapsule-SEG
NanoNet
LiTS2017
UNet 3+
ROBUST-MIS
Endotect Polyp Segmentation Challenge Dataset
DDANet
MoNuSAC
MaxViT-UNet
MoNuSeg 2018
MosMedData
C2FVL
PROMISE12
Hi-gMISnet
SegPC-2021
DCSAU-Net
Synapse
nnFormer
2015 MICCAI Polyp Detection
DoubleUNet
MICCAI 2015 Head and Neck Challenge
AnatomyNet
AMOS
MedNeXt-L (5x5x5)
iSEG 2017 Challenge
HyperDenseNet
Hyper-Kvasir Dataset
efficientnetb1
HSVM
MS-Dual-Guided
ASU-Mayo Clinic dataset
ResUNet++
Extended Task10_Colon Medical Decathlon
nnUNet
Autoimmune Dataset
Unet with APP
ENSeg
YOLOv8-m + SAM-b
Autooral dataset
HF-UNet
CHAOS MRI Dataset
MS-Dual-Guided
Cell