Medical Image Segmentation Techniques

NeuroMTL iSEG challenge methods

The paper presents a deep learning method for tissue classification in infant MRI scans and applies it to the iSeg-2017 challenge data.

MIMoSA: A Method for Inter-Modal Segmentation Analysis

MIMoSA improves automated white matter lesion segmentation in multiple sclerosis by integrating multimodal MRI data through inter-modal coupling regression and local logistic regression.

Comparison of different methods for average anatomical templates creation: do we really gain anything from a diffeomorphic framework?

This study compares diffeomorphic and non-diffeomorphic methods for creating average anatomical templates and finds that diffeomorphic frameworks do not necessarily improve accuracy.

A large, open source dataset of stroke anatomical brain images and manual lesion segmentations

The paper introduces ATLAS, a dataset of 304 T1-weighted MRIs with manual lesion segmentations to improve lesion segmentation algorithm accuracy.

The Brain/MINDS 3D digital marmoset brain atlas

The paper presents a 3D digital brain atlas of the common marmoset monkey with MRI and Nissl histology data, offering improved segmentation and file format for neuroscience research.

The Developing Human Connectome Project: a Minimal Processing Pipeline for Neonatal Cortical Surface Reconstruction

The paper introduces a fully automated pipeline for neonatal cortical surface reconstruction from MRI, achieving high accuracy in 85% of cases.

Unbiased construction of a temporally consistent morphological atlas of neonatal brain development

A linearly scaling groupwise method jointly estimates mean brain shape and longitudinal change across 275 neonates (35 to 44 weeks post-menstrual age), yielding a temporally consistent morphological atlas.

Transfer Learning for Task Adaptation of Brain Lesion Assessment and Prediction of Brain Abnormalities Progression/Regression using Irregularity Age Map in Brain MRI

This study uses an Irregularity Age Map to adapt transfer learning for brain lesion segmentation and predict WMH progression/regression without manual labels.

Unfolding the hippocampus: An intrinsic coordinate system for subfield segmentations and quantitative mapping

This paper introduces a computational method to unfold the hippocampus, enabling 2D mapping of subfields and revealing structural regularities validated by histology.

Multimodal Surface Matching with Higher-Order Smoothness Constraints

This paper introduces a new regularization method for cortical surface alignment in brain imaging, improving the robustness and biological interpretability of multi-modal data alignment.

Combining images and anatomical knowledge to improve automated vein segmentation in MRI

This study improves automated vein segmentation in MRI by combining susceptibility-weighted images, quantitative susceptibility maps, and a vein atlas into a composite vein image, showing significant performance gains.

Building a high-resolution in vivo minimum deformation average model of the human hippocampus

This paper develops a contrast matching algorithm to align MDA models of the human hippocampus with different contrasts, creating a high-resolution in vivo model for improved segmentation and disease detection.

A population MRI brain template and analysis tools for the macaque

The paper presents a high-resolution MRI template and analysis tools for macaque brains, enabling standardized processing and comparison across subjects and studies.

Mindcontrol: A Web Application for Brain Segmentation Quality Control

Mindcontrol is a web application that enables collaborative quality control of neuroimaging data through visualization, annotation, and integration with datasets.

Mindboggling morphometry of human brains

Open source Mindboggle pipeline extracts cortical folds, sulci and fundi and computes diverse shape measures, yielding normative morphometry for 101 manually labeled healthy human brains.