01558nas a2200229   4500000000100000008004100001653001900042653001200061653001300073653001500086653002000101100001400121700001500135700001300150700001100163700001300174700001500187245007200202856003700274300000800311520100900319       2024                            d10aChronic Wounds10aDataset10a Leprosy10aHealthcare10aMedical Imaging1 aSanchez K1 aHinojosa C1 aMieles O1 aZhao C1 aGhanem B1 aArguello H00aCO2Wounds-V2: Extended Chronic Wounds Dataset From Leprosy Patients  uhttps://arxiv.org/pdf/2408.10827  a1-73 a<p>Chronic wounds pose an ongoing health concern globally, largely due to the prevalence of conditions such as diabetes and leprosy’s disease. The standard method of monitoring these wounds involves visual inspection by healthcare professionals, a practice that could present challenges for patients in remote areas with inadequate transportation and healthcare infrastructure. This has led to the development of algorithms designed for the analysis and follow-up of wound images, which perform image-processing tasks such as classification, detection, and segmentation. However, the effectiveness of these algorithms heavily depends on the availability of comprehensive and varied wound image data, which is usually scarce. This paper introduces the CO2Wounds-V2 dataset, an extended collection of RGB wound images from leprosy patients with their corresponding semantic segmentation annotations, aiming to enhance the development and testing of image-processing algorithms in the medical field.</p>