Lung cancer is the abnormal growth of cells in the lung causing severe risk to human health because lung has a connected network of blood vessels and lymphatic channels vulnerable to metastasis. The survival rate of lung cancer greatly depends on the early detection and staging of the lung tumor. Computed Tomography (CT) images are widely used for lung tumor detection as they provide information about different parts of the lung. The accuracy of detecting tumor shape, location and volume plays a vital role in successful diagnosis and treatment of tumors. So, tumor detection and representation from three dimensional (3D) CT images are necessary to measure the tumor size properly and to detect the exact location of the tumor. Researchers introduced different methods for tumor nodule detection from two dimensional (2D) CT images, hence, the problems associated with such methods is the separation of lung from background and the differentiation of tumor from airways. This paper presents the use of neighborhood and connectivity properties of the CT image pixels to overcome these problems. In this work, several morphological processing used to remove background, noises and airways from the lung CT image and then the k-means clustering algorithms based segmentation used for lung tumor detection. The volumetric analysis of the lung nodules for the prediction of tumor stages performed according to the Tumor Nodule Metastasis (TNM) classification proposed by the World Health Organization (WHO). TNM for lung cancer uses the dimension, spreading and metastasis properties of the tumor. The lung tumor segmentation performed on a dataset named SPIE-AAPM Lung CT Challenge dataset collected from Washington University in St. Louis, which includes 22,489 CT images of 70 patients. The proposed scheme for 3D CT image segmentation and classification provides better performance in terms of accurate tumor detection and visualization of variant size, shape and location, less computation time and proper classification of tumor stages with an accuracy of 95.68%.

After the independence of Bangladesh (1971), new generation film development making take a place. Bangla commercial films can be divided before liberation, post liberation and modern era. Before liberation era; A. J. Kardar, Zahir Raihan, Khan Ataur Rahman, were the commercial Bengali film makers. During the Post liberation time, we have some extra ordinary movies like Sareng Bou (1978), Surjo Dighal Bari (1979) and so on. But in the modern era definition of commercial film has got a change. From 2009 to 2019 Bangladeshi audience got difference in commercial films. But having DT (Digital Technology) and other advancement given a development of Bangladeshi commercial film. But story making, acting, making, socialization and other things are gradually developing in Bangladeshi commercial films. This research will evaluate prospects and challenges of Bangladeshi commercial films from 2009 to 2019. However further research is recommended to develop making of Bangladeshi commercial films in respect of lifelike story, cultural dissemination and so on.