EnvoyAI Partner:

Year Founded: 2013
Area of Focus/Speciality: Change detection
Hospital Associations: N/A
Company Headquarters: Seattle, Washington
Number of Machines: 1
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A.I. Analysis Inc.

About A.I. Analysis Inc.

A.I. Analysis provides artificial intelligence tools to enhance radiologist performance. In particular, we provide tools for the detection and characterization of changes in serial medical imaging studies. We have published evidence that the change detector can reduce time to review serial imaging studies, can improve inter-observer agreement, and may be able to help radiologists to find changes months earlier than is possible using manual inspection, alone.

Press and Publications: 

  • Patriarche JW, Erickson BJ. “A review of the automated detection of change in serial imaging studies of the brain”. Journal of Digital Imaging 2004; 17(3):158-174. PMID15534751
  • Patriarche JW, Erickson BJ. "Part 1. Automated Change Detection and Characterization in Serial MR Studies of Brain Tumor Patients". Journal of Digital Imaging 2007; 20(3): 203-222. PMID17216385
  • Patriarche JW, Erickson BJ. "Part 2. Automated Change Detection and Characterization Applied to Serial MR of Brain Tumors May Detect Progression Earlier Than Human Experts". Journal of Digital Imaging 2007; 20(4): 321-328. PMID17216586
  • Khorasani R, Erickson BJ, Patriarche J. “New Opportunities in Computer-Aided Diagnosis: Change Detection and Characterization” Journal of the American College of Radiology 2006; 3(6): 468-469. PMID17412102
  • Erickson BJ, Mandrekar J, Wang L, Patriarche JW, Bartholmai BJ, Wood CP, Lindell EP, Sykes A-M, Harms GF, Lindell RM, Andriole K. “Effect of Automated Image Registration on Radiologist Interpretation”. Journal of Digital Imaging 2007; 20(2): 105-113. PMID17505869
  • Patriarche JW, Erickson BJ. “Change Detection & Characterization: a New Tool for Imaging
    Informatics and Cancer Research”. Cancer Informatics 2007; 1:1-11. PMID19390659
  • Erickson BJ, Patriarche JW, Wood CP, Campeau NG, Lindell EP, Savcenko V, Arslanlar N, Wang L. “Image Registration Improves Confidence and Accuracy of Image Interpretation”. Cancer Informatics 2007; 1:19-24. PMID19390661
  • Erickson BJ, Wood CP, Kaufmann TJ, Patriarche JW, Wang L, Mandrekar J. “Optimal Presentation Modes for Detecting Brain Tumor Progression.” American Journal of Neuroradiology 2011; 32(9):1652-7.
A.I. Analysis Leadership
Douglas Patriarche Co-founder

Douglas Patriarche


Julia Patriarche, Ph.D. Co-founder

Julia Patriarche, Ph.D.


A.I. Analysis Machine | Change Detector for Brain Imaging

A.I. Analysis is directly responsible for product and clinical representations

  • MS_T1+FLAIR.png

Detection and characterization of changes in serial medical
imaging studies. The core change detector uses a sophisticated
machine learning approach to correct for the normalization
differences that are inherent in acquisition types like magnetic
resonance imaging, so that the color coded change map
contains a correct assessment of what has changed, from 0.0
for no change, to +1.0 for maximal change in the positive
direction, to -1.0 for maximal change in the negative direction.

  • Applicable Study Types: MRI: Anatomical (including: T1-Pre, T1-Post, T2, FLAIR, PD, etc.). ADC, Perfusion (including: CBF, CBV, MTT, TTP)
  • Regulatory Status: Research use only