基于 IBIGP 算法的脑部早期异常检测

摘要

检出脑组织的早期异常增生往往是一项困难的工作。已有文献中提出了大量脑部异常检测算法，近十年来也出现了许多用于改进并简化异常组织检测的方法；不过在众多研究者看来，最具吸引力的技术或许还是基于磁共振成像（MRI）的算法。本文把一种称为归属个体高斯概率倒数（IBIGP）的技术应用于 MRI，以缓解脑组织早期异常检测的难题。研究表明，将 IBIGP 技术用于 MRI 图像，在早期检出脑 MRI 图像中的异常改变方面极为有效。该技术虽然尚处于起步阶段，但在提升脑部异常的早期检出上具有很大潜力。

Abstract

The detection of an incipient anomalous growth of tissue in a brain is often a difficult task. Various algorithms for brain anomalous detection have been suggested abundantly in the existing literature. In the last decade, many detection methods have been suggested to improve and facilitate abnormal tissue detection. However, the most attractive techniques to many researchers are maybe those that are magnetic resonance imagery (MRI)-based algorithms. A technique known as the inverse of the belonging individual Gaussian probability (IBIGP) is applied to MRI in this work in order to mitigate incipient anomalous tissue detection in a brain. This study demonstrates that the IBIGP technique, applied to the MRI image, is extremely effective in early detecting an anomalous change in the brain MRI image. Although this technique is still in its infancy, it has a great potential to enhance brain anomalous early detection.