01559nas a2200229 4500000000100000008004100001260001400042653002200056653001900078100001400097700001200111700001300123700001100136700001200147700001100159700001300170700001800183700001300201700001100214245005500225520104900280 2024 d bCRC Press10aScreening methods10aImage analysis1 aAgrawal P1 aAnand A1 aSharma M1 aPaul S1 aMohan J1 aRita E1 aDheeba J1 a Kalairassan 1 aMurali S1 aBiji C00aLeprosy Screening Through Image Processing Methods3 a
The paper attempts to investigate the possibility of developing leprosy screening methods through image analysis. The conventional diagnosis of leprosy is typically based on clinical evaluation and is highly subjective. Skin smears are used to screen patients for leprosy. The lab personnel used the smears to get morphological information viz bacilli shape and the clusters for grading the severity of the disease. The examination consumes time and demands skilled technicians especially when it is of a low bacterial load or even negative, as bacilli per field of view for the entire smear which consists of around 500 fields. Hence, the Image processing workflow is designed in detecting and counting the number of Mycobacterium leprae. The workflow involves two methods (i) Object detection through thresholding and (ii) Contour detection based on filtering. Finally, the Mycobacterium leprae are counted using the generated mask or contour to report the presence or absence of the bacilli and the level of severity of the disease.