DeepDerma

Fighting Melanoma With Deep Learning!

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Different factors participate in not diagnosing melanoma early enough

Melanoma is the most deadliest form of skin cancer

Clinical Presentation

The clinical presentation of melanoma is complex and diverse

Sometimes it is hard to distinguish moles from cancer

Subtleties and Nuances

Such melanoma subtypes are difficult to diagnose in a timely manner

Morphologic Subtypes

DeepDerma

From the fact that the likelihood of curing melanoma increases when diagnosed early and treated timely, DeepDerma emerged as a project that aims at developing Deep Learning based solutions that aid in the early detection of melanoma, and that would act as a powerful tool for use in clinical practice.

Publications

Paper No. 2

Paper No. 3

Paper No. 1

A systematic review of automated melanoma detection in dermatoscopic images and its ground truth data

In: Proc. SPIE, Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment, vol. 8318 (2012)In: Proc. SPIE, Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment, vol. 8318 (2012)

Melanoma Detection Using Deep Learning: A Systematic Review

Submitted (2018)

A Deep Learning Based Approach to Skin Lesion Border Extraction With a Novel Edge Detector in Dermoscopy Images

Submitted (2019)

Paper No. 4

Supervised Versus Unsupervised Deep Learning Based Methods for Skin Lesion Segmentation in Dermoscopy Images

Submitted (2019)

Abstract No. 1

Submitted (2019)

Abstract No. 2

Are Neural Networks Effective in Detecting Melanoma Using Genomic Data?

Submitted (2019)

A Deep Learning Approach to Deblurring Skin Cancer Images

Abder-Rahman Ali

Jingpeng Li

Guang Yang

Thomas Trappenberg

University of Stirling

University of Stirling

Imperial College London

Dalhousie University

Mater Private Hospital

Sally O'Shea

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