Human Lesion Detection Method Based on Image Information and Brain Signal

Abstract

The brain is the largest and most complex structure in the central nervous system. It dominates all activities in the body, and the lesions in the human body are also reflected in the brain signal. In this paper, the image method is used to assist the brain signal to detect the human lesion. Due to the particularity of medical images, there is no common segmentation method for any medical image, and there is no objective standard to judge whether the segmentation is effective. Medical image segmentation technology is still a bottleneck restricting the development and the application of other related technologies in medical image processing. Based on the above reasons, this paper proposes an improved region growing algorithm based on the fuzzy theory and region growing algorithm. The algorithm is used to segment the medical images of the liver and chest X-ray of different human organs. The improved algorithm uses a threshold segmentation algorithm to assist in the automatic selection of seed points and improves the region growing rules, then morphological post-processing is used to improve the segmentation effect. The experimental results show that the improved region growing algorithm has better segmentation effect under two different organs, which proves that the algorithm has certain applicability, and its accuracy and segmentation quality are better than the traditional region growing algorithm. This algorithm combines the advantages of the threshold method and traditional region growing method. It is feasible in algorithm and has certain application value. INDEX TERMS Medical image segmentation, improved region growing algorithm, applicability method, brain signal.

A Review on Brain Tumour Detection using Magnetic Resonance Imaging

“…The consequences of the proposed DWA-DNN strategy demonstrates that its precision and the factual measure is unquestionably more contending than some other non-profound learning procedures. Li, G., et al [4] the creators are proposed the accumulation and examination of brain sign to analyze the area of human injuries, because of its precision and natural effect, didn't accomplish great outcomes. In this paper, the restorative picture is dissected by picture handling, and the locale developing calculation is improved by improving the seed point choice strategy and district developing guideline of the customary area developing calculation.…”

“…In MRI Segmentation the Clustering segmentation procedure is most as often as possible utilized, in which the pixels is partitions into various parts having no earlier data or preparing [4]. It sorts the pixels having biggest likelihood into a similar class.…”

“…The threatening tumor spreads exceptionally quick and assaults other brain tissues and debilitates the wellbeing condition which more often than not causes even demise. The recognition of Brain tumor is testing issue for fundamental judgment on analysis, because of complex structure of brain [1]- [4]. The magnetic resonance imaging (MRI) pictures are utilized in medicinal imaging procedure, to give point by point data about the interior tissue of particular picture.…”

Concurrent fault diagnosis of modular multilevel converter with Kalman filter and optimized support vector machine

“…For decades, FD has proved to be a vitally important part contributing to safety critical systems. Compared to data-driven method (Li, Jiang, Zhou, Jiang, & Kong, 2019;Yuan, Zhang, Wu, Zhu, & Ding, 2017;Zheng, Mao, Liu, Wong, & Wang, 2016), the model-based FD approach has received particular attention due to the availability of physical models for many practical systems, and a great CONTACT Yong Zhang zhangyong77@wust.edu.cn number of excellent results have been reported in the literature, see e.g. Zhang, Wang, and Alsaadi (2018), Zhang, Wang, Ma, and Alsaadi (2019) and the references therein.…”

Image Stitching Based on Improved SURF Algorithm

“…Therefore, the method is simple and fast, but is easily interfered by the transition bandwidth, which causes the smoothness of the spliced image and the problem of ghosting, resulting in poor stability of the algorithm. The multi-band fusion algorithm proposed in is based on the idea of decomposing images in different frequencies, using different transition band widths for weighted interpolation processing and then performing fusion processing, although the image quality after stitching and fusion is good [2,3]. However, pictures with unevenly distributed features cannot be stitched together efficiently, and the algorithm has a large workload and a long calculation time, so the real-time performance is poor.…”