Problems associated with processing large numbers of chest radiographs.

Details

• Personal Author:
  Hankinson, John L. ; Stewart JE
• Description:
  The use of equal probability quantization in the automated interpretation of chest radiographs for pneumoconiosis was investigated. Nineteen chest radiograph pairs were scanned to give optimal gray level resolution. The images were transformed by equal probability quantization. Film texture measurements were taken before and after quantization. A much higher individual variation for film texture measurements occurred when the image was not transformed by equal probability quantization. Film texture relied heavily on film quality in those films which had not been normalized by equal probability quantization. Classification accuracy for normal and abnormal films was inconclusive. The authors conclude that individual variability of texture measurements is reduced by preprocessing the film with equal probability quantization. This preprocessing reduces the dependency of the texture measurements on film quality. [Description provided by NIOSH]
• Subjects:
  Diagnosis Occupational Health Radiation Radiography Respiratory System Respiratory Tract Diseases Safety
• Keywords:
  X-ray-analysis; X-ray-diagnosis; Radiography; Diagnostic-techniques; Occupational-respiratory-disease
• Document Type:
  Text
• Genre:
  Guidance
• Place as Subject:
  OSHA Region 3 ; West Virginia
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Division:
  DRDS - Division of Respiratory Disease Studies
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  1-3
• NIOSHTIC Number:
  nn:00118475
• Citation:
  NIOSH; :1-3
• Peer Reviewed:
  False
• Source Full Name:
  National Institute for Occupational Safety and Health
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:7dc847c09aedf140bc731323e8446b4703641ae07d6ad9e7b7238120dab30b8f7dcaa9b938d34d035f87873a0fe7fec262d5d13dcaf290925445e82b6de3b57d
• Download URL:
  https://stacks.cdc.gov/view/cdc/241323/cdc_241323_DS1.pdf
• File Type:
  [PDF - 168.02 KB ]