DEV Community

Cover image for AI Finds Best Method to Analyze Total-Body PET Scans, K-Means Clustering Leads the Pack
Mike Young
Mike Young

Posted on • Originally published at aimodels.fyi

AI Finds Best Method to Analyze Total-Body PET Scans, K-Means Clustering Leads the Pack

This is a Plain English Papers summary of a research paper called AI Finds Best Method to Analyze Total-Body PET Scans, K-Means Clustering Leads the Pack. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.

Overview

  • Study evaluates clustering algorithms for analyzing total-body PET scan data
  • Compares 4 major clustering methods: K-means, DBSCAN, OPTICS, and Hierarchical
  • Tests algorithms on both simulated and real patient PET imaging data
  • Develops quantitative metrics to assess clustering performance
  • Aims to automate analysis of dynamic PET scans for improved diagnosis

Plain English Explanation

Medical imaging helps doctors see inside the body to diagnose disease. PET scans are special images that show how different parts of the body use energy. These scans produce huge amounts of data...

Click here to read the full summary of this paper

API Trace View

How I Cut 22.3 Seconds Off an API Call with Sentry 🕒

Struggling with slow API calls? Dan Mindru walks through how he used Sentry's new Trace View feature to shave off 22.3 seconds from an API call.

Get a practical walkthrough of how to identify bottlenecks, split tasks into multiple parallel tasks, identify slow AI model calls, and more.

Read more →

Top comments (0)

Sentry image

See why 4M developers consider Sentry, “not bad.”

Fixing code doesn’t have to be the worst part of your day. Learn how Sentry can help.

Learn more