Imaging Informatics

9. Biomedical Imaging Informatics

After reading this chapter, you should know the answers to these questions: 1. What makes images a challenging type of data to be processed by computers, as opposed to non-image clinical data? 2. Why are there many different imaging modalities, and by what major two characteristics do they differ? 3. How are visual and knowledge content in images represented computationally? How are these techn...

Sensor, Signal, and Imaging Informatics.

Objective: To summarize significant contributions to sensor, signal, and imaging informatics published in 2016. Methods: We conducted an extensive search using PubMed® and Web of Science® to identify the scientific contributions published in 2016 that addressed sensors, signals, and imaging in medical informatics. The three section editors selected 15 candidate best papers by consensus. Each ca...

Overview of Medical Imaging Informatics

High-performance medical imaging informatics.

The topic of High Performance Medical Image Computing for Image-Assisted Clinical Intervention and Decision-Making is central for imaging informatics, since the amount and complexity of imaging data continues to grow as new modalities are added to the radiological repertoire in an increasingly distributed (and often cloud-computing) environment. This top ic was the subject of the 2010 High Perf...

High-throughput neuro-imaging informatics

This paper describes neuroinformatics technologies at 1 mm anatomical scale based on high-throughput 3D functional and structural imaging technologies of the human brain. The core is an abstract pipeline for converting functional and structural imagery into their high-dimensional neuroinformatic representation index containing O(1000-10,000) discriminating dimensions. The pipeline is based on a...