A general algorithm for recognizing small, vague, and imager-alike objects in a nonuniformly illuminated medical diagnostic image

Lee, S.C.; Wang, Yiming

doi:10.1109/acssc.1998.751401

Cited by 5 publications

(2 citation statements)

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“…These metrics seemed to vary with lesion type but were not integrated or applied to the segmentation of haemorrhages. A similar approach was proposed by LEE and WANG (1998)…”

Section: Exudate and Haemorrhage Segmentationmentioning

confidence: 99%

Progress towards automated diabetic ocular screening: A review of image analysis and intelligent systems for diabetic retinopathy

Teng

Lefley

Claremont

2002

Med. Biol. Eng. Comput.

165

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Patients with diabetes require annual screening for effective timing of sight-saving treatment. However, the lack of screening and the shortage of ophthalmologists limit the ocular health care available. This is stimulating research into automated analysis of the reflectance images of the ocular fundus. Publications applicable to the automated screening of diabetic retinopathy are summarised. The review has been structured to mimic some of the processes that an ophthalmologist performs when examining the retina. Thus image processing tasks, such as vessel and lesion location, are reviewed before any intelligent or automated systems. Most research has been undertaken in identification of the retinal vasculature and analysis of early pathological changes. Progress has been made in the identification of the retinal vasculature and the more common pathological features, such as small aneurysms and exudates. Ancillary research into image preprocessing has also been identified. In summary, the advent of digital data sets has made image analysis more accessible, although questions regarding the assessment of individual algorithms and whole systems are only just being addressed.

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“…These metrics seemed to vary with lesion type but were not integrated or applied to the segmentation of haemorrhages. A similar approach was proposed by LEE and WANG (1998)…”

Section: Exudate and Haemorrhage Segmentationmentioning

confidence: 99%

Progress towards automated diabetic ocular screening: A review of image analysis and intelligent systems for diabetic retinopathy

Teng

Lefley

Claremont

2002

Med. Biol. Eng. Comput.

165

View full text Add to dashboard Cite

show abstract

“…Several attempts have been made to detect hard exudates using histogram segmentation. If the background color of a retinal image is sufficiently uniform, a simple and effective method to separate exudates from the background is to select proper thresholds [10,15,18]. [11,14] investigate dynamic thresholding by dividing a retinal image into sub-images and computing a threshold based on the local histogram.…”

Section: Related Workmentioning

confidence: 99%