Reconsidering bit depth for medial images: Is eight enough?

Based on observations made at our institution that diagnostic images could be read on cathode ray tube (CRT) displays controlled with 8-bit hardware, a reconsideration of the bit depth for primary interpretation of radiological images seemed in order. Using actual CRT performance and human visual system (HVS) models with target size, surround luminance and external noise parameters (detector, display and image), CRT luminance modulation as a function of bit depth is compared with the HVS detection threshold modulation. While best case HVS performance requires, at least, 10-bit control to avoid creating luminance artifacts, probable HVS performance is estimated when targets are small, surround luminance is not equal to target luminance and external noise is included as a mask. In this light, the HVS threshold modulation is elevated to such an extent that 8-bit hardware is sufficient. It is shown that when implemented in 8-bit space at the display, the DICOM display function standard creates additional noise and potentially, artifacts. Acceptable image display in an 8-bit space will be discussed with respect to display data representation alternatives such gamma space, which is based on the intrinsic (uncorrected) CRT display function.

[1]  Ehsan Samei,et al.  Optimal display processing for digital radiography , 2001, SPIE Medical Imaging.

[2]  Peter G. J. Barten,et al.  Contrast sensitivity of the human eye and its e ects on image quality , 1999 .

[3]  Michael J. Flynn,et al.  High-resolution, high-performance radiographic film scanner , 1990, Medical Imaging.

[4]  Thomas Mertelmeier,et al.  Impact of phosphor luminance noise on the specification of high-resolution CRT displays for medical imaging , 1997, Medical Imaging.

[5]  Edward Muka,et al.  Human visual system intrascene luminance dynamic range , 2002, SPIE Medical Imaging.

[6]  Richard A. Normann,et al.  Photoreceptor contributions to contrast sensitivity: Applications in radiological diagnosis , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[7]  Richard L. Van Metter,et al.  Visual study of perceptually optimized displays , 1997, Medical Imaging.

[8]  E. Peli In search of a contrast metric: Matching the perceived contrast of gabor patches at different phases and bandwidths , 1997, Vision Research.

[9]  Scott J. Daly,et al.  Visible differences predictor: an algorithm for the assessment of image fidelity , 1992, Electronic Imaging.

[10]  A van Meeteren,et al.  Effects of pictorial noise interfering with visual detection. , 1988, Journal of the Optical Society of America. A, Optics and image science.

[11]  E. Peli,et al.  Contrast sensitivity function and image discrimination. , 2001, Journal of the Optical Society of America. A, Optics, image science, and vision.

[12]  Edward Muka,et al.  Image quantization: statistics and modeling , 1998, Medical Imaging.

[13]  竹本 宜弘 JPEG (Joint Photographic Experts Group) , 1995 .