Method for optimizing planning and placement of probes in brain via multi-modal 3D analysis of brain anatomy

A method includes obtaining a first imaging scan and a second imaging scan of a brain of a single subject. The first imaging scan is converted into a first data set and the second imaging scan is converted into a second data set. A sequence adaptive multi-modal segmentation algorithm is applied to t...

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Bibliographic Details
Main Authors KADIPARSAOGLU, MUSTAFA, FAN KEVIN, ROLLO, PHILIP, S, FORSYTH KEVIN, DONOS CHRISTOS, TANDON NILANJAN
Format Patent
LanguageChinese
English
Published 09.12.2022
Subjects
CALCULATING
COMPUTING
COUNTING
DIAGNOSIS
HUMAN NECESSITIES
HYGIENE
IDENTIFICATION
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
MEASURING
MEASURING ELECTRIC VARIABLES
MEASURING MAGNETIC VARIABLES
MEDICAL OR VETERINARY SCIENCE
PHYSICS
SURGERY
TESTING
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Summary:A method includes obtaining a first imaging scan and a second imaging scan of a brain of a single subject. The first imaging scan is converted into a first data set and the second imaging scan is converted into a second data set. A sequence adaptive multi-modal segmentation algorithm is applied to the first data set and the second data set. A sequence adaptive multi-modal segmentation algorithm performs automatic intensity-based tissue classification to generate a first tagged data set and a second tagged data set. The first tagged data set and the second tagged data set are automatically co-registered with each other to generate a transformation matrix based on the first tagged data set and the second tagged data set. A transformation matrix is applied to align the first data set and the second data set. 一种方法包括：获得单个受试者脑部的第一成像扫描和第二成像扫描。第一成像扫描被转换为第一数据集，并且第二成像扫描被转换为第二数据集。将序列自适应多模态分割算法应用于第一数据集和第二数据集。序列自适应多模态分割算法执行自动基于强度的组织分类，以生成第一标记数据集和第二标记数据集。第一标记数据集和第二标记数据集自动彼此共同配准，以基于第一标记数据集和第二标记数据集生成变换矩阵。变换矩阵被应用，以对齐第一数据集和第二数
Bibliography:Application Number: CN20218029295