On the concept of objectivity in digital image analysis in pathology

Methods: First, a brief background on the basic science of image analysis in histology details some of the controversies and opinions in the field. Then, a literature review of a subset of papers pertaining to image analysis in histology (with claims of objectivity) is conducted to determine what evidence exists for objectivity in these methods. Results: It was found that image analysis may have many benefits (speed, indefatigability, standardisation, etc.). However, algorithms are devised and implemented by human beings who make subjective decisions at each stage of the algorithm design and implementation process. Thus, image analysis methods can be seen as deterministic processes which 'objectively' implement the subjective decisions of the programmer. This indicates that 'inter-observer' variation in image analysis is equivalent to 'inter-algorithm' variation (which is rarely studied) and that a single computer algorithm's repeatability is of lesser importance than the repeatability of the image analysis method as a whole (including the block, slide and field selection and the method of tissue processing). Conclusion: Repeatability and automaticity must not be confused with objectivity, but a lack of objectivity does not imply a lack of utility. Unless specific evidence of objectivity is provided, editors should insist that claims of objectivity in image analysis papers be either removed or justified prior to publication.