Lesion-TOADS

Lesion-TOADS extends the TOADS approach to brains with WM lesions. In addition to providing a detail segmentation of brain structures, Lesion-TOADS also provides a delineation of WM lesions. The segmentation of the structures is topologically correct even in the presence of the WM lesions.

Input Types

Lesion-TOADS requires T1-weighted and FLAIR images for the segmentation. The input images should be skull stripped and have a correct information header.

Module Parameters

Main inputs

Atlas file	A text file providing the location of the atlases, as well as the predefined clustering parameters for each input pulse sequence.
Output images	Specifies the type of the output images that are desirable. hard segmentation Outputs the topologically constrained hard segmentation of the brain. It also outputs the lesion segmentation in a separate file. In the hard segmentation, WM lesions are included in the WM unless specified otherwise (see lesion options below). hard segmentation +memberships In addition to the hard segmentation of lesions and structures, it also provides the fuzzy memberships for all the brain structures  as well as the WM lesions in a 4D image. cruise inputs In addition to the hard segmentation of lesions and structures, it outputs the sulcal CSF, filled WM, and cortical GM memberships, as well as the filled WM mask.  These are necessary for CRUISE algorithm to reconstruct the cortical surfaces. dura removal inputs Similar to cruise inputs but it also includes the cerebellum memberships. These inputs are necessary for Remove Dura algorithm.
Output max membership classification	In addition to the topologically constrained segmentation, it also provides the hard segmentation computed directly from fuzzy memberships without any constraint.
Correct inhomogeneity	Models the inhomogeneity by a low degree polynomial in the clustering algorithm.
Output inhomogeneity field	Outputs the estimated inhomogeneity field (if correct inhomogeneity option is selected)

Lesion Options

Maximum GM Distance Maximum Ventricle Distance Maximum InterVentricular Distance	Maximum distance from the GM, ventricle, and inter ventricular WM boundary to correct the lesion membership to decrease the common false positives in the lesion segmentation.
Include lesions in hard segmentation	Associates the lesions with a separate label in the hard segmentation

Advanced Options

Atlas prior	Controls the influence of the statistical atlases on the segmentation algorithm.
Smoothing parameter	Controls the amount of the spatial smoothness imposed on the fuzzy memberships.
Maximum difference	Convergence criteria that specifies the minimum amount of relative change in the energy function.
Maximum iterations	Maximum number of iterations before the algorithm stops.
Atlas alignment	The type of transformation used for registering the statistical atlases to the subject space. rigid This is the default option and generates the most robust results. multi_fully_affine A more elaborate registration that can be used if rigid registration does not generate good results.
Connectivity (foreground,background)	The connectivity rule use for defining the simple points in digital topology.

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Example Usage

Input images	MPRAGE T1-weighted FLAIR
Hard segmentation and lesion segmentation.	Hard Segmentation Lesion Segmentation Hard Segmentation with Lesions included
Membership functions	Ventricles Caudate Cerebral WM
Cruise Inputs	Cortical GM Filled WM Filled WM mask