Fusion of Deep Learning with Conventional Imaging Processing: Does It Bring Artificial Intelligence Closer to the Clinic?-Reference-Cited by-同舟云学术

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Fusion of Deep Learning with Conventional Imaging Processing: Does It Bring Artificial Intelligence Closer to the Clinic?

Published:2024-07 Issue:7 Volume:144 Page:1424-1427
ISSN:0022-202X
Container-title:Journal of Investigative Dermatology
language:en
Short-container-title:Journal of Investigative Dermatology

Author:

Hagerty Jason R.^ORCID,Nambisan Anand,Stanley R. Joe^ORCID,Stoecker William V.

Publisher

Elsevier BV

Reference9 articles.

1. Melanoma and nevus skin lesion classification using handcraft and deep learning feature fusion via mutual information measures;Almaraz-Damian;Entropy (Basel),2020

2. Fusion between an algorithm based on the characterization of melanocytic lesions’ asymmetry with an ensemble of convolutional neural networks for melanoma detection;Collenne;J Invest Dermatol,2024

3. Hagerty JR, Stanley RJ, Stoecker WV. Medical image processing in the age of deep learning - is there still room for conventional medical image processing techniques? Paper presented in: International Conference on Computer Vision Theory and Applications. 27 February to 1 January 2017; Porto, Portugal.

4. SharpRazor: automatic removal of hair and ruler marks from dermoscopy images;Kasmi;Skin Res Technol,2023

5. Skin lesion segmentation in dermoscopic images with noisy data;Lama;J Digit Imaging,2023

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