Bag-of-Features Classification Model for the Diagnose of Melanoma in Dermoscopy Images Using Color and Texture Descriptors-Reference-Cited by-同舟云学术

Bag-of-Features Classification Model for the Diagnose of Melanoma in Dermoscopy Images Using Color and Texture Descriptors

Published:2013 Issue: Volume: Page:547-555
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
Short-container-title:

Author:

Barata Catarina,Marques Jorge S.,Mendonça Teresa

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-39094-4_62

Reference16 articles.

1. Argenziano, G., et al.: Interactive atlas of dermoscopy (2000)

2. Iyatomi, H., et al.: An improved internet-based melanoma screening system with dermatologist-like tumor area extraction algorithm. CMIG 32(7), 566–579 (2008)

3. Celebi, M., et al.: Automatic detection of blue-white veil and related structures in dermoscopy images. CMIG 32(8), 670–677 (2008)

4. Barata, C., et al.: A system for the detection of pigment network in dermoscopy images using directional filters. IEEE TBME 59(10), 2744–2754 (2012)

5. Stolz, W., et al.: ABCD rule of dermatoscopy: a new practical method for early recognition of malignant melanoma. Euro. J. Dermatology 4, 521–527 (1994)

Cited by 26 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dynamic Attribute-guided Few-shot Open-set Network for medical image diagnosis;Expert Systems with Applications;2024-10

2. Image Steered Super Resolution based Melonoma Cancer Detection;2023 OITS International Conference on Information Technology (OCIT);2023-12-13

3. Fine-tuning pre-trained neural networks for medical image classification in small clinical datasets;Multimedia Tools and Applications;2023-08-31

4. Classification of Skin Lesions by Incorporating Drop-Block and Batch Normalization Layers in Representative CNN Models;Arabian Journal for Science and Engineering;2023-07-28

5. Enhanced U-Net segmentation with ensemble convolutional neural network for automated skin disease classification;Knowledge and Information Systems;2023-06-05