Automatic lesion boundary detection in dermoscopy
This addresses a domain-specific problem in medical imaging for dermatology, but it appears incremental as it adapts an existing method to a new application.
The paper tackles automatic lesion boundary detection in dermoscopy by adapting a U-net convolutional neural network with skip connections for segmentation, aiming to serve as an experiment and benchmark for deep learning in biomedical tasks.
This manuscript addresses the problem of the automatic lesion boundary detection in dermoscopy, using deep neural networks. An approach is based on the adaptation of the U-net convolutional neural network with skip connections for lesion boundary segmentation task. I hope this paper could serve, to some extent, as an experiment of using deep convolutional networks in biomedical segmentation task and as a guideline of the boundary detection benchmark, inspiring further attempts and researches.