Skin tumour detection plays a key factor in medical research. Nowadays, tumour detection process is of crucial importance as the number of persons affected is increasing substantially. The aim of this research work is to develop a new approach for efficient image enhancement and tumour detection from other unaffected regions on computed tomographic skin images. This work is mainly related to medical application methods on computed tomography (CT) skin tumour images that have been designed and implemented efficiently. The initial method, which was based on the quality of image, enhanced the medical image performance. Normally, these images are very noise sensitive and create difficulty in handling procedures. Proper care has to be taken which involves the introduction of pre-processing algorithms like enhancement techniques and filters. According to this, Anisotropic Diffusion Filtering (ADF) followed by Recursive Mean Separate Histogram Equalization (RMSHE) algorithm was introduced to improve the contrast of tumour images. In the second method, Public Contour Metric Based Segmentation (PCMBS) Mapping and Prioritized Patch Based Region Segmentation (PPBRS) Algorithm is proposed for skin tumour segmentation. These techniques are performed in CT skin tumour image which are benign or malignant. Overall accuracy of 98.5% and 95.4% is obtained for various benign and malignant tumours, respectively, in MATLAB 2018a software.

皮肤肿瘤检测在医学研究中起着关键作用。如今，随着受影响人数的大幅增加，肿瘤检测过程变得至关重要。这项研究工作的目的是开发一种新方法，用于在计算机断层扫描皮肤图像上从其他未受影响的区域进行有效的图像增强和肿瘤检测。这项工作主要涉及有效设计和实施的计算机断层扫描（CT）皮肤肿瘤图像的医学应用方法。最初基于图像质量的方法提高了医学图像的性能。通常，这些图像对噪声非常敏感并且在处理过程中造成困难。必须采取适当的措施，包括引入预处理算法，如增强技术和过滤器。据此，引入各向异性扩散滤波（ADF）和递归平均分离直方图均衡（RMSHE）算法来提高肿瘤图像的对比度。在第二种方法中，提出了基于公共轮廓度量的分割（PCMBS）映射和基于优先块的区域分割（PPBRS）算法用于皮肤肿瘤分割。这些技术是在良性或恶性的CT皮肤肿瘤图像中进行的。在 MATLAB 2018a 软件中，各种良性和恶性肿瘤的总体准确率分别为 98.5% 和 95.4%。提出了基于公共轮廓度量的分割（PCMBS）映射和基于优先块的区域分割（PPBRS）算法用于皮肤肿瘤分割。这些技术是在良性或恶性的CT皮肤肿瘤图像中进行的。在 MATLAB 2018a 软件中，各种良性和恶性肿瘤的总体准确率分别为 98.5% 和 95.4%。提出了基于公共轮廓度量的分割（PCMBS）映射和基于优先块的区域分割（PPBRS）算法用于皮肤肿瘤分割。这些技术是在良性或恶性的CT皮肤肿瘤图像中进行的。在 MATLAB 2018a 软件中，各种良性和恶性肿瘤的总体准确率分别为 98.5% 和 95.4%。