Detection of Breast Cancer using MRI: A Pictorial Essay of the Image Processing Techniques

Abstract

Medical imaging generates the visual representation of the interior body parts for the clinical analysis/ medical intervention. Now a days, an advanced medical imaging technique i.e. MRI provides acute dissection anatomical information about the human soft tissues. MRI generally suffers from poor contrast, low quality due to improper brightness & blurriness. So contrast manipulation is compulsively needed. Image enhancement is taken as the initial step which defines the accuracy of result. The prime objective is to enhance the visual appearance for further image analysis i.e. detection, segmentation, feature extraction/selection and even classification. Out of all the current image enhancement methods, the appropriate choice must be influenced by the facts i.e. visual perspective, modality and climatic conditions. The noise model and the filter reconstruction mainly decide the trade-off between noise reduction and feature preservation of the original image. In this paper, Median filter (MF), Average filter (AF), Wiener Filter (WF) and Gaussian filter (GF) are used to compare the effects of most dominant noises in MR images by calculating the statistical parameters i.e. Mean Square Error, PSNR, RMSE and MAE. Also, the MR images impinge with the variable noise density for effective comparative analysis of the filters. Further, the proposed algorithm detected the tumor region appropriately.

Breast Cancer Classification based on Artificial Intelligence: State of the Art

“…Consequently, the utilisation of an image filter is employed to augment the visual data encapsulated within the input images [18]. Among the many types of filters that are put to use, the median filter, the Gaussian filter, and the adaptive median filter stand out [19,20,21]. The primary objective of employing a filter in the context of image processing is to enhance the overall quality of the image while accentuating its edges The primary objective of employing a filter in the context of image processing is to enhance the overall quality of the image while accentuating its edges [22].…”

ROI Selection Criteria for Finding the Abnormal Tissues from Breast Magnetic Resonance Imaging

“…Breast malignancy is the most well-known disease in ladies and long haul therapeutic viability of careful mediation relies upon precise staging of tumor malignant growth [1]. The size of tumor is the prime feature to forecast the breast cancer.…”

An Intelligent Educational System for Breast Cancer Management"

“…It is a disease that is deadly in many cases, has touched many people's lives, and will continue to do so in the future. Breast cancer is the main cause of disease mortality among women [10].…”

“…The final decision was made as a result of the diagnosis of three parts of breast cancer. Since diagnosing breast cancer consists of three parts of the proposed system: diagnosing by symptoms, diagnosing from image processing, and diagnosing by breast biopsy, each of which is an independent event, the final decision probability can be given by the probability of A multiplied by the probability of B multiplied by the probability of C. As an example, [26]: (10) Where: A, B, and C are events of the probability The probability of event A, as assigned by the set function P, is represented by the set function P (A). The probability of event B, as assigned by the set function P, is represented by the set function P (B).…”