Bioinspired polarization imaging sensors: From circuits and optics to signal processing algorithms and biomedical applications

Timothy York, Samuel B. Powell, Shengkui Gao, Lindsey Kahan, Tauseef Charanya, Debajit Saha, Nicholas W. Roberts, Thomas W. Cronin, Justin Marshall, Samuel Achilefu, Spencer P. Lake, Baranidharan Raman, Viktor Gruev

Research output: Contribution to journalArticlepeer-review


In this paper, we present recent work on bioinspired polarization imaging sensors and their applications in biomedicine. In particular, we focus on three different aspects of these sensors. First, we describe the electro-optical challenges in realizing a bioinspired polarization imager, and in particular, we provide a detailed description of a recent low-power complementary metal-oxide-semiconductor (CMOS) polarization imager. Second, we focus on signal processing algorithms tailored for this new class of bioinspired polarization imaging sensors, such as calibration and interpolation. Third, the emergence of these sensors has enabled rapid progress in characterizing polarization signals and environmental parameters in nature, as well as several biomedical areas, such as label-free optical neural recording, dynamic tissue strength analysis, and early diagnosis of flat cancerous lesions in a murine colorectal tumor model. We highlight results obtained from these three areas and discuss future applications for these sensors.

Original languageEnglish (US)
Article number6880796
Pages (from-to)1450-1469
Number of pages20
JournalProceedings of the IEEE
Issue number10
StatePublished - Oct 1 2014
Externally publishedYes


  • Bioinspired circuits
  • Calibration
  • Complementary metal-oxide-semiconductor (CMOS) image sensor
  • Current-mode imaging
  • Interpolation
  • Neural recording
  • Optical neural recording
  • Polarization

ASJC Scopus subject areas

  • General Computer Science
  • Electrical and Electronic Engineering


Dive into the research topics of 'Bioinspired polarization imaging sensors: From circuits and optics to signal processing algorithms and biomedical applications'. Together they form a unique fingerprint.

Cite this