BACKGROUND: The diagnostic ability of algorithms developed for the Multispectral Digital Colposcope (MDC) is highly dependent on the quality of the image. The field of objective medical image quality analysis has great potential but has not been well exploited. Various researchers have reported different measures of image quality but with an existence of a reference image. The quality of an image can be attributed to several sources of errors, a few of which would be inclusion of presence of extraneous components, improper illumination, or an image out of focus. This can be due to motion artifact or the region of interest out of the focal plane. METHODS: With spectroscopic measurements, assessment of data quality has been used by our group in the past to avoid hardware errors at the time of acquisition. We are currently developing algorithms that will help identify hardware and acquisition errors to the clinician in under a few seconds. RESULTS: Minimizing these errors not only provides quality images for a diagnostic algorithm, but reduces the necessity for complex and time intensive post-processing software for enhancing the images. CONCLUSION: We propose a no reference image quality system specifically designed for MDC that can be modified to similar spectroscopic imaging applications.
BACKGROUND: The diagnostic ability of algorithms developed for the Multispectral Digital Colposcope (MDC) is highly dependent on the quality of the image. The field of objective medical image quality analysis has great potential but has not been well exploited. Various researchers have reported different measures of image quality but with an existence of a reference image. The quality of an image can be attributed to several sources of errors, a few of which would be inclusion of presence of extraneous components, improper illumination, or an image out of focus. This can be due to motion artifact or the region of interest out of the focal plane. METHODS: With spectroscopic measurements, assessment of data quality has been used by our group in the past to avoid hardware errors at the time of acquisition. We are currently developing algorithms that will help identify hardware and acquisition errors to the clinician in under a few seconds. RESULTS: Minimizing these errors not only provides quality images for a diagnostic algorithm, but reduces the necessity for complex and time intensive post-processing software for enhancing the images. CONCLUSION: We propose a no reference image quality system specifically designed for MDC that can be modified to similar spectroscopic imaging applications.
Authors: Christopher T Lam; Marlee S Krieger; Jennifer E Gallagher; Betsy Asma; Lisa C Muasher; John W Schmitt; Nimmi Ramanujam Journal: PLoS One Date: 2015-09-02 Impact factor: 3.240
Authors: Timon P H Buys; Scott B Cantor; Martial Guillaud; Karen Adler-Storthz; Dennis D Cox; Clement Okolo; Oyedunni Arulogon; Oladimeji Oladepo; Karen Basen-Engquist; Eileen Shinn; José-Miguel Yamal; J Robert Beck; Michael E Scheurer; Dirk van Niekerk; Anais Malpica; Jasenka Matisic; Gregg Staerkel; Edward Neely Atkinson; Luc Bidaut; Pierre Lane; J Lou Benedet; Dianne Miller; Tom Ehlen; Roderick Price; Isaac F Adewole; Calum MacAulay; Michele Follen Journal: Gend Med Date: 2011-09-22
Authors: Scott B Cantor; Jose-Miguel Yamal; Martial Guillaud; Dennis D Cox; E Neely Atkinson; John L Benedet; Dianne Miller; Thomas Ehlen; Jasenka Matisic; Dirk van Niekerk; Monique Bertrand; Andrea Milbourne; Helen Rhodes; Anais Malpica; Gregg Staerkel; Shahla Nader-Eftekhari; Karen Adler-Storthz; Michael E Scheurer; Karen Basen-Engquist; Eileen Shinn; Loyd A West; Anne-Therese Vlastos; Xia Tao; J Robert Beck; Calum Macaulay; Michele Follen Journal: Int J Cancer Date: 2010-11-09 Impact factor: 7.396
Authors: Jose-Miguel Yamal; Getie A Zewdie; Dennis D Cox; E Neely Atkinson; Scott B Cantor; Calum MacAulay; Kalatu Davies; Isaac Adewole; Timon P H Buys; Michele Follen Journal: J Biomed Opt Date: 2012-04 Impact factor: 3.170