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

Assessment of Diffusion and Perfusion

Assessment of Diffusion and Perfusion

Understanding and evaluating diffusion and perfusion is critical in assessing a patient's respiratory and circulatory health. These processes play key roles in maintaining the body's internal environment, ensuring that tissues receive adequate oxygen while waste products are efficiently removed.
The Role of Diffusion in Respiration
Diffusion is the process by which molecules move from an area of higher concentration to an area of lower concentration. In the respiratory system, this...

You might also read

Related Articles

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

Sort by

Same author

Extending Regression Without Truth to Integrate Ground-Truth Measurements for Evaluating Quantitative Imaging Methods with Patient Data.

Proceedings of SPIE--the International Society for Optical Engineering·2026

Same author

NGSE-Corr: A technique for objective clinical evaluation of quantitative-imaging methods without a gold standard.

IEEE transactions on medical imaging·2026

Same author

Progress in SPECT and PET Reconstruction for Theranostics: From Diagnosis to Therapy.

ArXiv·2025

Same author

Nuclear Medicine AI in Action: The Bethesda Report (AI Summit 2024).

Journal of nuclear medicine : official publication, Society of Nuclear Medicine·2025

Same author

Advances in SPECT and PET Reconstruction for Theranostics: From Diagnosis to Therapy.

PET clinics·2025

Same author

What Is Implementation Science: And Why It Matters for Bridging the Artificial Intelligence Innovation-to-Application Gap in Medical Imaging.

PET clinics·2025

Search research articles

Related Experiment Video

Updated: Mar 27, 2026

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Published on: December 15, 2014

A maximum-likelihood method to estimate a single ADC value of lesions using diffusion MRI.

Abhinav K Jha¹, Jeffrey J Rodríguez², Alison T Stopeck³

¹Division of Medical Imaging Physics, Department of Radiology and Radiological Sciences, Johns Hopkins Medical Institutions, Baltimore, Maryland, USA.

Magnetic Resonance in Medicine

|January 9, 2016

Summary

A new maximum-likelihood method accurately estimates apparent diffusion coefficient (ADC) in lesions using diffusion MRI. This fast, rigorous technique outperforms existing methods for lesion characterization.

Keywords:

ADC estimation maximum-likelihood method motion misalignment single ADC value statistics of Rician-distributed random variables

More Related Videos

A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia

A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia

Published on: September 16, 2017

Diffusion Imaging in the Rat Cervical Spinal Cord

Diffusion Imaging in the Rat Cervical Spinal Cord

Published on: April 7, 2015

Related Experiment Videos

Last Updated: Mar 27, 2026

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Published on: December 15, 2014

A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia

A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia

Published on: September 16, 2017

Diffusion Imaging in the Rat Cervical Spinal Cord

Diffusion Imaging in the Rat Cervical Spinal Cord

Published on: April 7, 2015

Area of Science:

Medical Imaging
Diffusion MRI Physics
Quantitative MRI

Background:

Diffusion MRI is crucial for characterizing tissue microstructure.
Estimating a single apparent diffusion coefficient (ADC) for lesions is vital for diagnosis and monitoring.
Lesion heterogeneity and signal-to-noise ratio (SNR) pose challenges for accurate ADC estimation.

Purpose of the Study:

To develop a statistically rigorous method for estimating a single apparent diffusion coefficient (ADC) of a lesion from its mean signal intensity in diffusion MRI.
To compare the proposed method against conventional linear-regression and state-of-the-art ADC-map techniques.

Main Methods:

A maximum-likelihood technique was derived, incorporating lesion intensity statistics and accounting for heterogeneity.
Performance was evaluated using realistic simulations with homogeneous and heterogeneous lesion models, including patient data.
Comparisons were made with linear-regression and ADC-map techniques across various parameters.

Main Results:

The proposed maximum-likelihood technique demonstrated superior performance over linear-regression and ADC-map methods.
Outperformance was observed across a wide range of SNR, ADC values, lesion sizes, and misalignment parameters.
The method proved effective even with varying b-values and lesion heterogeneity, executing in under one second.

Conclusions:

A rigorous, computationally efficient, and user-friendly maximum-likelihood technique for single lesion ADC estimation was successfully developed.
The proposed method offers a robust and accurate approach for quantitative analysis in diffusion MRI.
Results strongly support the clinical utility and reliability of this novel ADC estimation technique.