Alam, Dr. Md. AshrafulPavel, Monirul IslamSadique, Ashique MohammadRitul, Rifat AhmedKhan, SynthiaNath, Snigdha2018-01-152018-01-1520178/21/2017ID 14301141ID 12201103ID 13101205ID 13101006ID 14101125http://hdl.handle.net/10361/9060Cataloged from PDF version of thesis report.Includes bibliographical references (pages 51-53).This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.We proposed cancer cell detection using image processing techniques based on cancer cell counting, cell area measurement and clump detection. The proposed system autonomously detects traits of cancer in microscopy images of biopsy samples. Previous similar attempts lack flexibility in terms of features and the level of accuracy is not consistent on respective type of cancer. The system pre-processes the input image by means of gray scaling, binarization, inversion, median filtering and flood fill operation. The pre-processed image then undergoes "cell counting", "area measurement" or "clump detection" depending on the type of trait to be detected. Several sets of images were processed using this methodology and the system was fine-tuned using the feedback from these test runs. The proposed method can be effectively used for autonomous cancer cell detection, which will significantly accelerate cancer cell researches and open up new dimensions.53 pagesenBRAC University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.Cancer detectionImage processingCellDigital image processingThesis