CVFeb 26, 2017

Spatially Aware Melanoma Segmentation Using Hybrid Deep Learning Techniques

arXiv:1702.07963v118 citations
Originality Synthesis-oriented
AI Analysis

This work addresses melanoma segmentation for medical diagnosis, but it appears incremental as it builds on existing deep learning techniques without introducing a major breakthrough.

The paper tackled the problem of accurately segmenting skin lesions in medical images by proposing a hybrid deep learning method combining convolutional and recurrent neural networks, achieving results on the ISBI 2017 challenge dataset with 1800 training and 150 test images.

In this paper, we proposed using a hybrid method that utilises deep convolutional and recurrent neural networks for accurate delineation of skin lesion of images supplied with ISBI 2017 lesion segmentation challenge. The proposed method was trained using 1800 images and tested on 150 images from ISBI 2017 challenge.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes