• Skip to main content
  • Skip to after header navigation
  • Skip to site footer
ERN: Emerging Researchers National Conference in STEM

ERN: Emerging Researchers National Conference in STEM

  • About
    • About AAAS
    • About the NSF
    • About the Conference
    • Partners/Supporters
    • Project Team
  • Conference
  • Abstracts
    • Undergraduate Abstract Locator
    • Graduate Abstract Locator
    • Abstract Submission Process
    • Presentation Schedules
    • Abstract Submission Guidelines
    • Presentation Guidelines
  • Travel Awards
  • Resources
    • Award Winners
    • Code of Conduct-AAAS Meetings
    • Code of Conduct-ERN Conference
    • Conference Agenda
    • Conference Materials
    • Conference Program Books
    • ERN Photo Galleries
    • Events | Opportunities
    • Exhibitor Info
    • HBCU-UP/CREST PI/PD Meeting
    • In the News
    • NSF Harassment Policy
    • Plenary Session Videos
    • Professional Development
    • Science Careers Handbook
    • Additional Resources
    • Archives
  • Engage
    • Webinars
    • ERN 10-Year Anniversary Videos
    • Plenary Session Videos
  • Contact Us
  • Login

Image Processing in Nanorobotics For Medical Applications

Undergraduate #310
Discipline:
Subcategory: Computer Science & Information Systems

Kamali Lowe - Hampton University


There is an emerging branch of technological research that focuses on the construction of nanorobots (nanobots). The creation of nanobots has a potential to revolutionize modern medicine in diagnosis, treatment and eventually a cure for disease. One aspect is to have a nanobot with enough complexity to enter a human body and to capture imaging of benign and cancerous cells internally. This research will investigate various approaches where nanorobotics can be used to conduct MRI and biopsy for cancer treatment. With an assumption that a robot can take a picture, would the nanobot able to process the image while it is in the body, or would it has to send an image to be processed by a computer with higher computing capability. Existing image processing algorithms (such as, Gradient Vector Flow and Color-Based Image Segmentation Using K-mean Clustering) will be investigated and selected image processing algorithms will be implemented. An enhanced, light-weighted version algorithm will be developed for the nanobot. A comparison between a traditional image processing and a light-weight version will be included in this presentation.

Funder Acknowledgement(s): This research is supported by grant from NSF HRD-1238838.

Faculty Advisor: Chutima Boonthum-Denecke, Chutima.Boonthum@hamptonu.edu

Role: Research algorithms of various types.

Sidebar

Abstract Locators

  • Undergraduate Abstract Locator
  • Graduate Abstract Locator

This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

AAAS

1200 New York Ave, NW
Washington,DC 20005
202-326-6400
Contact Us
About Us

  • LinkedIn
  • Facebook
  • Instagram
  • Twitter
  • YouTube

The World’s Largest General Scientific Society

Useful Links

  • Membership
  • Careers at AAAS
  • Privacy Policy
  • Terms of Use

Focus Areas

  • Science Education
  • Science Diplomacy
  • Public Engagement
  • Careers in STEM

Focus Areas

  • Shaping Science Policy
  • Advocacy for Evidence
  • R&D Budget Analysis
  • Human Rights, Ethics & Law

© 2023 American Association for the Advancement of Science