Title :
Tuberculosis bacilli detection in Ziehl-Neelsen-stained tissue using affine moment invariants and Extreme Learning Machine
Author :
Osman, M.K. ; Mashor, M.Y. ; Jaafar, H.
Author_Institution :
Fac. of Electr. Eng., Univ. Teknol. MARA (UiTM), Bukit Mertajam, Malaysia
Abstract :
This paper describes an approach to automate the detection and classification of tuberculosis (TB) bacilli in tissue section using image processing technique and feedforward neural network trained by Extreme Learning Machine. It aims to assist pathologists in TB diagnosis and give an alternative to the conventional manual screening process, which is time-consuming and labour-intensive. Images are captured from Ziehl-Neelsen (ZN) stained tissue slides using light microscope as it is commonly used approach for diagnosis of TB. Then colour image segmentation is used to locate the regions correspond to the bacilli. After that, affine moment invariants are extracted to represent the segmented regions. These features are invariant under rotation, scale and translation, thus useful to represent the bacilli. Finally, a single layer feedforward neural network (SLFNN) trained by Extreme Learning Machine (ELM) is used to detect and classify the features into three classes: `TB´, `overlapped TB´ and `non-TB´. The results indicate that the ELM gives acceptable classification performance with shorter training period compared to the standard backpropagation training algorithms.
Keywords :
biomedical optical imaging; diseases; image segmentation; medical image processing; neural nets; optical microscopy; TB diagnosis; Ziehl-Neelsen stained tissue slide; Ziehl-Neelsen-stained tissue; affine moment invariants; colour image segmentation; extreme learning machine; image processing; light microscopy; single layer feedforward neural network; tuberculosis bacilli detection; Classification algorithms; Image color analysis; Image segmentation; Machine learning; Microscopy; Signal processing algorithms; Training; Extreme Learning Machine; Tuberculosis bacilli detection; affine moment invariants; neural network; tissue sections;
Conference_Titel :
Signal Processing and its Applications (CSPA), 2011 IEEE 7th International Colloquium on
Conference_Location :
Penang
Print_ISBN :
978-1-61284-414-5
DOI :
10.1109/CSPA.2011.5759878