Those terms are commonly used in image processing e.g. comparing reproductivity of given segmentation method. Their meaning is as fallow:
Inter-observer - one observer scores the same phenomena several times at different times. For example: few times the same radiologist selects region of interest (ROI) on the same X-ray. The question is, how similar those selections separated in time are to each other i.e. can the radiologists manually select exactly the same ROI in terms of position, shape, size?
Intra-observer - few observers score the same phenomena. For instance: few radiologists select manually ROI on the same X-ray. What is the agreement in selected ROI by different radiologists.
Observer bias - each observer can interpret the same phenomena differently. For example, if selecting ROI, radiologist can include into ROI distorted parts of an X-ray image (e.g. by noise), because for him those distortions are small. At the same time, the other radiologists can avoid those parts of X-ray, cause for him those distortions are to serious to ignore.
Inter-observer - one observer scores the same phenomena several times at different times. For example: few times the same radiologist selects region of interest (ROI) on the same X-ray. The question is, how similar those selections separated in time are to each other i.e. can the radiologists manually select exactly the same ROI in terms of position, shape, size?
Intra-observer - few observers score the same phenomena. For instance: few radiologists select manually ROI on the same X-ray. What is the agreement in selected ROI by different radiologists.
Observer bias - each observer can interpret the same phenomena differently. For example, if selecting ROI, radiologist can include into ROI distorted parts of an X-ray image (e.g. by noise), because for him those distortions are small. At the same time, the other radiologists can avoid those parts of X-ray, cause for him those distortions are to serious to ignore.
