Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Cluster Sampling Method

Cluster Sampling Method

Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...

Area Computation by the Alternative Coordinate Method

Area Computation by the Alternative Coordinate Method

The alternative coordinate method, also known as the Shoelace Formula, is a technique for determining the area of a traverse using Cartesian coordinates. This method relies on the sequential arrangement of x and y coordinates for each point of the shape, ensuring accuracy and ease of application.In this approach, each corner's x and y coordinates are listed as fractions, with the x-coordinate as the numerator and the y-coordinate as the denominator. These coordinates are arranged sequentially...

Statistical Methods for Analyzing Epidemiological Data

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:

Biostatistics: Overview

Biostatistics: Overview

Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
Discrete variables are...

Statistical Software for Data Analysis and Clinical Trials

Statistical Software for Data Analysis and Clinical Trials

Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...

Methods of Obtaining Topography

Methods of Obtaining Topography

Topography involves measuring and mapping land elevations, natural features, and artificial structures to create accurate representations of the terrain. Topographic surveying relies on traditional and modern methods, each with distinct advantages and limitations.Traditional Surveying Methods:Transit stadia surveys and plane table surveys were widely used traditional surveying methods. These techniques relied on instruments like theodolites and stadia rods for measuring distances and angles,...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

An MRI Atlas of the Human Fetal Brain: Reference and Segmentation Tools for Fetal Brain MRI Analysis.

Scientific data·2026

Same author

Harmonization in magnetic resonance imaging: A survey of acquisition, image-level, and feature-level methods.

Medical image analysis·2026

Same author

Brain volumes in fetuses with congenital heart disease and placental vascular abnormalities.

Journal of perinatology : official journal of the California Perinatal Association·2026

Same author

Advances in automated fetal brain MRI segmentation and biometry: Insights from the FeTA 2024 challenge.

Medical image analysis·2026

Same author

LesionSCynth: A simple parametric lesion synthesis method to improve spinal cord lesion segmentation in low-data scenarios.

Imaging neuroscience (Cambridge, Mass.)·2025

Same author

Insights into Temporal and Spatial Dynamics of Short Association Fiber Formation in the Human Fetal Brain.

bioRxiv : the preprint server for biology·2025

Same journal

Genetic Impacts on Variability of Body Fat Distribution Uncover Gene-Environment and Gene-Gene Interactions.

bioRxiv : the preprint server for biology·2026

Same journal

16S ribosomal RNA modification drives transcript-specific translation efficiency.

bioRxiv : the preprint server for biology·2026

Same journal

FlcE latches onto the FliL-stator complex to turbocharge flagellar motility in <i>Borrelia burgdorferi</i>.

bioRxiv : the preprint server for biology·2026

Same journal

Synaptic pruning, myelination and the emergence of psychiatric disorders in late adolescence.

bioRxiv : the preprint server for biology·2026

Same journal

Structural and functional insights into the Rcs phosphorelay.

bioRxiv : the preprint server for biology·2026

Same journal

The structural basis of RanGAP1 regulation and catalysis in nuclear transport.

bioRxiv : the preprint server for biology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jul 21, 2025

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography

Published on: August 11, 2016

TBSS++: A novel computational method for Tract-Based Spatial Statistics.

Davood Karimi¹, Hamza Kebiri^1,2, Ali Gholipour¹

¹Computational Radiology Laboratory (CRL), Department of Radiology, Boston Children's Hospital, and Harvard Medical School, USA.

Biorxiv : the Preprint Server for Biology

|July 28, 2023

Summary

This summary is machine-generated.

This study introduces a new computational framework for analyzing brain white matter using diffusion-weighted magnetic resonance imaging (dMRI). The improved method enhances the accuracy and reproducibility of cross-subject tract-specific analyses in neuroscience research.

Keywords:

Diffusion MRI TBSS brain white matter deep learning tract-based spatial statistics

More Related Videos

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

Role of Diffusion MRI Tractography in Endoscopic Endonasal Skull Base Surgery

Role of Diffusion MRI Tractography in Endoscopic Endonasal Skull Base Surgery

Published on: July 5, 2021

Related Experiment Videos

Last Updated: Jul 21, 2025

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography

Published on: August 11, 2016

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

Role of Diffusion MRI Tractography in Endoscopic Endonasal Skull Base Surgery

Role of Diffusion MRI Tractography in Endoscopic Endonasal Skull Base Surgery

Published on: July 5, 2021

Area of Science:

Neuroimaging
Computational Neuroscience
Biomedical Engineering

Background:

Diffusion-weighted magnetic resonance imaging (dMRI) is crucial for brain white matter assessment.
Cross-subject tract-specific analysis in dMRI requires precise comparison of white matter tracts, which is challenging with existing methods like Tract-Based Spatial Statistics (TBSS).
Limitations in current methods can compromise the validity of dMRI-derived biomarker studies.

Approach:

Developed a novel computational framework for dMRI analysis.
Incorporated accurate white matter tract segmentation and precise registration based on fiber orientation distributions.
Created detailed white matter tract atlases to serve as an unbiased reference space for cross-subject data alignment.

Key Points:

The new framework significantly improves the accuracy of white matter tract segmentation and registration.
Utilizes fiber orientation distributions for precise cross-subject data alignment.
Employs detailed white matter atlases as a standardized reference space.

Conclusions:

The proposed framework demonstrates superior reproducibility and robustness compared to existing methods like TBSS.
Offers a substantial advancement in the accuracy and reliability of cross-subject dMRI studies.
Promises to enhance the quality of neuroscience and medical research relying on dMRI analysis.