Automated detection of Mycobacterium tuberculosis using transfer learning - Abdullahi Umar Ibrahim; Emrah Guler; Meryem Guvenir; Kaya Suer; Sertan Serte; Mehmet Ozsoz (Journal of Infection in Developing Countries)
Introduction: Quantitative analysis of Mycobacterium tuberculosis using microscope is very critical for diagnosing tuberculosis diseases. Microbiologist encounter several challenges which can lead to misdiagnosis. However, there are 3 main challenges: (1) The size of Mycobacterium tuberculosis is very small and difficult to identify as a result of low contrast background, heterogenous shape, irregular appearance and faint boundaries (2) Mycobacterium tuberculosis overlapped with each other making it difficult to conduct accurate diagnosis (3) Large amount of slide can be time consuming and tedious to microbiologist and which can lead to misinterpretations.