m-VGG16: a dermoscopy image segmentation method based on VGG16

Linyi Zheng; YuXing Dai

doi:10.1117/12.2660011

3 February 2023 m-VGG16: a dermoscopy image segmentation method based on VGG16

Linyi Zheng, YuXing Dai

Proceedings Volume 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022); 1251114 (2023) https://doi.org/10.1117/12.2660011
Event: Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 2022, Hulun Buir, China

Abstract

Skin cancer is one of the most commonly diagnosed types of cancer and poses a great threat to people's health. By using computer-aided diagnosis, the corresponding lesions of skin cancer can be classified and segmented. With the development of deep learning in recent years, the convolutional neural network based on deep learning provides a better diagnostic aid for traditional manual selection and empirical judgment under heuristic rules. In this paper, an improved m-VGG16 network model is proposed through the network structure based on VGG16. It uses the U-shaped structure in the U-net model to complete the structural design of the model, and initializes the m-VGG16 network with the weights of the pretrained VGG16 model on the ImageNet dataset. In this paper, experiments were performed on the dermoscopy image dataset from the Part1 part of the ISIC 2017 challenge to test the performance of the model by the corresponding evaluation metrics. There is a certain improvement in Jaccard Index compared to the comparison model, which provides a worthwhile reference for research on aspects related to dermatoscopic image segmentation.

Citation Download Citation

Linyi Zheng and YuXing Dai "m-VGG16: a dermoscopy image segmentation method based on VGG16", Proc. SPIE 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 1251114 (3 February 2023); https://doi.org/10.1117/12.2660011

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KEYWORDS

Image segmentation

Data modeling

Skin cancer

RGB color model

Medical imaging

Visual process modeling

Convolution

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