findprls: MS Lesion Identification and PRL Classification with...

In carolynlou/prlr: MS Lesion Identification and PRL Classification

Description

This function takes in a lesion probability map, a lesion segmentation mask, and a T2*-phase image for a single subject and identifies + classifies lesions as PRL or not.

Usage

findprls(probmap, lesmask, phasefile, disc = T)

Arguments

probmap	Lesion probability map. We recommend using lesion segmentation algorithm MIMoSA.
lesmask	Lesion segmentation mask. Given a probability threshold, automatically binarizes lesion probability map into a segmentation mask.
phasefile	Location of the T2*-phase image
disc	Calculate discretized versions of first order radiomic features?

Value

A list with 3 objects: a NIfTI file of a lesion label map, a dataframe containing all radiomic features, and a vector containing lesion-wise probability of being a PRL

carolynlou/prlr documentation built on Oct. 2, 2020, 10:28 a.m.