Study of feature extraction for diagnosing prostate cancer

As the number of patient with prostate cancer increases, the computer aided diagnosis support for prostate cancer become important. Traditional computer-based method checks the detailed texture of the image, but the proposed method focuses on area and relation of position from a broader field of view approximating the way of diagnosis is made by pathologist. As a result, average of the glands´ inner area seems significant for classifying Gleason Grade.