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This paper introduces an algorithm for the automated diagnosis of referable maculopathy in retinal images for diabetic retinopathy screening. Referable maculopathy is a potentially sight-threatening condition requiring immediate referral to an ophthalmologist from the screening service, and therefore accurate referral is extremely important. The algorithm uses a pipeline of detection and filtering...
Skin lesion pigmentation area from surface, or, epi-illumination (ELM) images and blood volume area from transillumination (TLM) images are useful features to aid a dermatologist in the diagnosis of melanoma and other skin cancers in early curable stages. However, segmentation of these areas is difficult. In this work, we present an automatic segmentation tool for ELM and TLM images that also provides...
Automating the detection of lesions in liver CT scans requires a high performance and robust solution. With CT-scan start to become the norm in emergency department, the need for a fast and efficient liver lesions detection method is arising. In this paper, we propose a fast and evolvable method to profile the features of pre-segmented healthy liver and use it to detect the presence of liver lesions...
The large number of false positives that result when automatic algorithms are considered for segmenting small multiple sclerosis lesions in magnetic resonance imaging hampers the posterior evaluation of lesion load. To address this problem we propose a fuzzy system which can improve the differentiation between true and false positive detections in proton density- and T2-weighted images. On the basis...
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