Volumetric parameterization of the placenta to a flattened template

Related tags

Deep Learningplacenta-flattening
Overview

placenta-flattening

A MATLAB algorithm for volumetric mesh parameterization. Developed for mapping a placenta segmentation derived from an MRI image to a flattened template for visualization. The code can work on NIFTI images or MATLAB matrices containing imaging information.

Requirements

Add the MATLAB packages to the working path.

Usage

main(grayImage, segImage): input a grayscale MRI image and the corresponding binary segmentation, where voxels labeled '1' correspond to the placenta. The inputs grayImage, segImage can either be full path locations of NIFTI image files, or image matrices. The grayImage input can be a 3D MRI volume, or a 4D series of MRI volumes. The script outputs the flattened meshes and images containing the mapped intensities.

Development

Please contact Mazdak Abulnaga, [email protected].

Citing and Paper

Please consider citing our paper

@inproceedings{abulnaga2019placenta,
title={Placental Flattening via Volumetric Parameterization},
author={Abulnaga, S. Mazdak and Abaci Turk, Esra and Bessmeltsev, Mikhail and Grant, P. Ellen and Solomon, Justin and Golland, Polina},
booktitle={Medical Image Computing and Computer Assisted Intervention -- MICCAI 2019},
year={2019},
pages={39--47},
}
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Comments
  • Is it possible to provide public input data?

    Is it possible to provide public input data?

    Hello, I am a master student majoring in computer science. I am very interested in your work and hope to reproduce the results, but because there is no MRI scan data, I cannot successfully run the program to observe the effect. If you can provide the program input data, I will really appreciate.

    opened by yuemos 3
  • 4d

    4d

    Now accepts 4D input grayscale images as input. Implemented by adding a loop when mapping the MRI images to the flattened space. I've tested with 4D nifti input, but not 4D image matrices.

    opened by PaddySlator 0
Releases(v1.0.0)
Owner
Mazdak Abulnaga
CS PhD student at MIT
Mazdak Abulnaga
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