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In this paper a simple and computationally efficient approach as per the complexity has been presented for Automatic Skin Lesion Segmentation using a Deep Learning architecture called SegNet including some additional specifications for the improvisation of the results.
SOTA for Skin Cancer Segmentation on PH2
In this paper, we propose a Recurrent Convolutional Neural Network (RCNN) based on U-Net as well as a Recurrent Residual Convolutional Neural Network (RRCNN) based on U-Net models, which are named RU-Net and R2U-Net respectively.
SOTA for Retinal Vessel Segmentation on STARE
Road extraction from aerial images has been a hot research topic in the field of remote sensing image analysis.
#2 best model for Skin Cancer Segmentation on Kaggle Skin Lesion Segmentation
There is large consent that successful training of deep networks requires many thousand annotated training samples.
SOTA for Cell Segmentation on PhC-U373
CELL SEGMENTATION COLORECTAL GLAND SEGMENTATION: ELECTRON MICROSCOPY IMAGE SEGMENTATION IMAGE AUGMENTATION LESION SEGMENTATION LUNG NODULE SEGMENTATION MULTI-TISSUE NUCLEUS SEGMENTATION PANCREAS SEGMENTATION RETINAL VESSEL SEGMENTATION SEMANTIC SEGMENTATION SKIN CANCER SEGMENTATION