Dermatoscope image melanoma segmentation method and device and related components
A melanoma and dermoscopy technology, applied in the field of computer-aided medicine, can solve the problems of inaccurate segmentation and poor segmentation efficiency, and achieve the effect of inaccurate segmentation, accurate boundary, fast and effective automatic segmentation
Active Publication Date: 2021-10-26
SHENZHEN UNIV
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[0005] The purpose of the present invention is to provide a melanoma segmentation method, device and related components in dermoscopic images, aiming to solve the problems of inaccurate and poor segmentation efficiency in the segmentation of lesion areas in dermoscopic images
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[0031] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0032] It should be understood that when used in this specification and the appended claims, the terms "comprising" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude one or Presence or addition of multiple other features, integers, steps, operations, elements, components and / or collections thereof.
[0033] It should also be understood that the terminology used in th...
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The invention discloses a dermatoscope image melanoma segmentation method, a dermatoscope image melanoma segmentation device and related components. The method comprises the following steps: performing feature extraction on a dermatoscope sample image through a pre-trained Res2Net model to generate low-level features and high-level features; performing cross-layer feature fusion on the low-level features and the high-level features to obtain a global mapping graph; performing convolution on the advanced features by using different voidage rates, and guiding an intermediate prediction map obtained by convolution by using a global mapping map to obtain a final prediction map; using a loss function to supervise and optimize the final prediction map, the intermediate prediction map and the global mapping map at the same time to obtain an optimized dermatoscope image melanoma segmentation model; and segmenting the dermatoscope detection image by using the dermatoscope image melanoma segmentation model, and outputting a segmentation result. According to the method, the melanoma area of the dermatoscope image can be automatically segmented quickly and effectively, and the boundary of the output segmentation result is accurate.
Description
technical field [0001] The present invention relates to the field of computer-aided medicine, in particular to a method, device and related components for melanoma segmentation of dermoscopic images. Background technique [0002] Malignant melanoma is not obvious in the early stage, and it is difficult for experienced clinicians to predict directly with the naked eye, but dermoscopy is the best way to check melanoma, and dermoscopy imaging technology has become the first choice for malignant melanoma. Effective tool for clinical diagnosis. [0003] Dermoscopy, also known as epidermal light transmission microscope, skin surface microscope, incident light microscope, etc., is a non-invasive skin microscopic image analysis technology, using oil immersion, light and optical magnification equipment, can observe including the lower part of the epidermis It is an effective tool for diagnosing melanoma and other colored skin lesions mainly by detecting skin structures invisible to ...
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Login to View More IPC IPC(8): G06T7/11G06K9/46G06K9/62G06N3/08
CPCG06T7/11G06N3/084G06T2207/10061G06T2207/20081G06T2207/30088G06T2207/30096G06F18/253
Inventor 岳广辉李思莹周天薇周恒韩婉婉李苑汪天富
Owner SHENZHEN UNIV