• Archives
  • Cryptocurrency
  • Earnings
  • Enterprise
  • About TechBooky
  • Submit Article
  • Advertise Here
  • Contact Us
TechBooky
  • African
  • AI
  • Metaverse
  • Gadgets
Generic selectors
Exact matches only
Search in title
Search in content
Post Type Selectors
  • African
  • AI
  • Metaverse
  • Gadgets
Generic selectors
Exact matches only
Search in title
Search in content
Post Type Selectors
TechBooky
Generic selectors
Exact matches only
Search in title
Search in content
Post Type Selectors
Home Artificial Intelligence

Researchers Develop AI Model That Classifies Brain Tumours With Single MRI Scan

Ayoola by Ayoola
August 12, 2021
in Artificial Intelligence, Medical
Share on FacebookShare on Twitter

According to a story published in science journal: Radiology: Artificial Intelligence , Washington University School of Medicine researchers, using Artificial intelligence has developed a model that would help classify the tumour of the brain with a single 3D MRI scan.

A new breakthrough in medicine you say?

You may be right after all!

According to a joint statement by Satrajit Chakrabarty, M.S., a doctoral student, and Daniel Marcus, Ph.D. from the  Washington University School of Medicine in St. Louis, Missouri, who formed part of the research team: “This is the first study to address the most common intracranial tumours and to directly determine the tumour class or the absence of tumour from a 3D MRI volume”.

High-grade glioma, low-grade glioma , brain metastases, meningioma, pituitary adenoma and acoustic neuroma, six of the most common types of tumour were documented through the process called his pathology, wherein tissues are surgically removed from a suspected cancer cell and examined with the use of a microscope.

Chakrabarty while analysing how MRI data would be used to automatically detect and classify brain tumours said:

“Non-invasive MRI may be used as a complement, or in some cases, as an alternative to histopathologic examination,”

The researchers from the Mallinckrodt Institute of Radiology , together with Chakrabarty built a massive, multi-institutional intracranial MRI scans 3D datasets through a convolutional neural network, obtaining pre-operative, post contrast T1-weighted MRI scans using the Brain Tumour Image Segmentation, The Cancer Genome Atlas Glioblastoma Multiforme, and The Cancer Genome Atlas Low Grade Glioma processes.

2,105 total scans were then grouped into three data subsets, with 1.396 of it for training, 261 scans for internal testing while 348 scans was for external testing. The performances of the model suing data from the external and internal MRI scans were evaluated after the first MRI scan set were used to train the convolutional neural network to separate healthy scans and unhealthy ones that has tumours, helping the classification of tumour type.

With the use of the internal testing data, a 93.35 percent accuracy was gotten from a healthy class and six tumour class with a accuracy figure of 337 out of 361.

Positive Predictive Value, with sensitivities ranging from 91 percent to 100 percent, has the probability of patients who had hitherto had a positive screening test having the disease ranging from 85 percent to 100 percent.

On the other hand, Negative Predictive Value ranged from 98 percent to 100 percent across all the classes with network attention overlapping with the tumour areas for all tumour types.

For the external test dataset, which included only two tumour types (high-grade glioma and low-grade glioma), the model had an accuracy of 91.95%.

According to Chakrabarty ,“These results suggest that deep learning is a promising approach for automated classification and evaluation of brain tumours. The model achieved high accuracy on a heterogeneous dataset and showed excellent generalization capabilities on unseen testing data.”

He further added that  the 3D deep learning model aligns more to the goal of an end-to-end, automated workflow where existing 2D models are improved upon, a process that requires radiologists to manually delineate, or characterize, the tumour area on an MRI scan before machine processing.

According to Dr. Sotiras, who is a co-developer of the model, the method can be extended to other brain tumour types or neurological disorders, potentially providing a pathway to augment much of the neuroradiology workflow.

“This network is the first step toward developing an artificial intelligence-augmented radiology workflow that can support image interpretation by providing quantitative information and statistics,” Chakrabarty added.

 

 

Reference: “MRI-based Identification and Classification of Major Intracranial Tumour Types Using a 3D Convolutional Neural Network: A Retrospective Multi-Institutional Analysis” 11 August 2021, Radiology: Artificial Intelligence.

Related Posts:

  • nvidia
    DiffUHaul, an AI Tool from Nvidia Research, Enables…
  • WHAM-BlogHeroFeature-1400×788-1
    Unveiling the Microsoft Muse AI Model & Its Features
  • galactica_screenshot
    Meta Shuts Down Public Test Of Galactica, Its ‘AI…
  • DotOrg_2_1.width-1200.format-webp
    Google.org Pledges $20M for AI Science Research
  • Deepmind-Robotics-Chatbot-Business-2021265856
    Google Forms New Team to Develop AI To Replicate Real World
  • meta-releases-ai-model-that-can-check-other-ai-models–work—–dkp5wbl4d6jt06dz8hki9f
    Meta Develops AI to Evaluate Other AI Models
  • Microsoft-datacenter-cold-aisle-server-racks-for-the-AMD-MI300X
    Microsoft Prepares for OpenAI's GPT-5 Launch
  • meta-and-spotify-ceos-unite-against-eu-ai-data-restrictions
    CEOs of Meta and Spotify Lament Over AI Regulations…

Discover more from TechBooky

Subscribe to get the latest posts sent to your email.

Tags: AIartificial intelligencebrainmedicalmriresearch
Ayoola

Ayoola

Ayoola Faseyi, an Abuja based Journalist with interest in Technology and Politics. He is a versatile writer with articles in many renowned News Journals.He is the Co-Founder of media brand, The Vent Republic.

BROWSE BY CATEGORIES

Select Category

    Receive top tech news directly in your inbox

    subscription from
    Loading

    Freshly Squeezed

    • TikTok adds YouTube Music Integration for Videos July 29, 2025
    • Globacom Starts Network Upgrade To Improve Service Quality July 29, 2025
    • WhatsApp Tests Night Mode for Android Camera July 29, 2025
    • Google Chrome Adds AI Store Summaries for Shopping July 29, 2025
    • Harmonic Launches Aristotle AI Chatbot App July 29, 2025
    • Steam, Itch.io Pressure Visa and Mastercard over Adult Game Restrictions July 29, 2025

    Browse Archives

    July 2025
    MTWTFSS
     123456
    78910111213
    14151617181920
    21222324252627
    28293031 
    « Jun    

    Quick Links

    • About TechBooky
    • Advertise Here
    • Contact us
    • Submit Article
    • Privacy Policy
    Generic selectors
    Exact matches only
    Search in title
    Search in content
    Post Type Selectors
    • African
    • Artificial Intelligence
    • Gadgets
    • Metaverse
    • Tips
    • About TechBooky
    • Advertise Here
    • Submit Article
    • Contact us

    © 2025 Designed By TechBooky Elite

    Discover more from TechBooky

    Subscribe now to keep reading and get access to the full archive.

    Continue reading

    We use cookies to ensure that we give you the best experience on our website. If you continue to use this site we will assume that you are happy with it.