Knowledge-aware deep framework for collaborative skin lesion segmentation and melanoma recognition
Deep learning techniques have shown their superior performance in dermatologist clinical inspection. Nevertheless, melanoma diagnosis is still a challenging task due to the difficulty of incorporating the useful dermatologist clinical knowledge into the learning process. In this paper, we propos...
Saved in:
Main Authors: | Wang, Xiaohong, Jiang, Xudong, Ding, Henghui, Zhao, Yuqian, Liu, Jun |
---|---|
Other Authors: | School of Electrical and Electronic Engineering |
Format: | Article |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/161419 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Artifact removal and lesion segmentation for melanoma detection in skin lesion images
by: Salido, Julie Ann A., et al.
Published: (2018) -
Skin lesion (melanoma) segmentation
by: Ong, Shi Quan
Published: (2021) -
Subungual melanoma: A study of 124 cases highlighting features of early lesions, potential pitfalls in diagnosis, and guidelines for histologic reporting
by: Tan, K.-B., et al.
Published: (2016) -
Adaptive responses as mechanisms of resistance to braf inhibitors in melanoma
by: Saei, A., et al.
Published: (2021) -
Retinoids: Formulation development and efficacy evaluation in melanoma cells
by: LIU XIN
Published: (2010)