Table 10 An overview of the datasets and challenges related to skin, phantom, and animal image analysis tasks.
From: Revolutionizing healthcare: a comparative insight into deep learning’s role in medical imaging
Dataset | Year | Techniques | Emphasis |
|---|---|---|---|
DFU 2020165 | 2020 | RGB | Detection of foot ulcers in diabetic patients |
ISIC 2019166 | 2019 | RGB | Classification of 9 diseases |
MATCH167 | 2020 | CT | Tumor tracking in lung |
MRI-DIR168 | 2018 | MR, CT | Multi-modality registration with phantom |
CC-Radiomics-Phantom-2169 | 2018 | CT | Feature assessment with phantom |
PET-Seg Challenge170 | 2016 | CT, PET | Phantom registration and research |
EndoVis 2019 SCARED171 | 2019 | Endoscopy | Depth estimation from endoscopic data |
BigNeuron172 | 2016 | General microscopy | Animal neuron reconstruction |
SNEMI3D173 | 2013 | Electron microscope | Segmentation of neurites |
Learn2Reg174 | 2020 | MR, CT | Image registration |
