eng Oriental Scientific Publishing Company Biomedical and Pharmacology Journal 0974-6242 2017-12-21 10 4 2035 2043 10.13005/bpj/1325 17895 article Ammi Reddy Pulagam 1 Venkata Krishna Rao Ede 2 Ramesh Babu Inampudi 3 Vasireddy Venkatadri Institute of Technology, Nambur, Guntur, AP, India. Lakireddy Bali Reddy College of Engineering, Mylavaram, Vijayawada, AP, India. Acharya Nagrjuna University, Nagarjuna Nagar Guntur, AP, India. Traditional statistical thresholding algorithms use only class variance sum as a standard for threshold selection. These algorithms overlook characteristics of surrounding thin airways and fail to obtain without leakage. The airways are the leakage of fluid into the surrounding lung parenchyma which would result in low contrast between the airways and the lung parenchyma due to noise or pathologies.  We propose, a novel criterion combining the class variance sum and discrepancy of variances in between thin airways and lung parenchyma to eliminate the described drawback for traditional statistical process.  After that, we use morphological methods to identify candidate airways on CT slices and then reconstruct a connected three dimensional airway tree.  Extensive validation work was done using Lung TIME database. The experimental airway test results substantial increase number of branches and total tree length. From inspiration scans on the mean number of branches detected is 46.5%, the tree length detected is 42.33% and the number of false positives is 0.28%. https://biomedpharmajournal.org/vol10no4/segmentation-of-airways-in-lung-region-using-novel-statistical-thresholding-and-morphology-methods/ Computed Tomography Lung Region Segmentation Airways