Automatic Identification of Lung and Colon Cancer Cells Based on CNN and YOLO Algorithms

作     者：达为（José David Zambrano Jara） 

作者单位：哈尔滨理工大学 

学位级别：硕士

导师姓名：孙博文

授予年度：2022年

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 1002[医学-临床医学] 081104[工学-模式识别与智能系统] 08[工学] 080203[工学-机械设计及理论] 100214[医学-肿瘤学] 0835[工学-软件工程] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 10[医学] 

摘      要：Can deep learning help in providing reliable early cancer detection? Expert systems based on Deep Learning can be used to make an early diagnosis,offering a second opinion or a preliminary diagnosis,hence reducing the mortality rate of cancer *** though cancer is considered one of the most serious health problems,its cause still remains unknown,making it a major problem *** access to specialized health services is not affordable or easy to obtain and regular medical check-ups are not frequent,disease detection is prone to happen in the advanced stages where the symptoms have become noticeable and ***’s why creating and developing new technologies have become crucial keys in reducing the mortality rate of *** study proposes a model based on Depthwise Convolutional Networks for the classification of Lung and Colon Cancerous Cells,tested on 3 different datasets using ADAM,ADAGRAD,“SGD+Nesterov,and“SGD+MOMENTUM optimizers for the main model,and a secondary expert model who will verify the predictions in cases where the calculation doesn’t reach a minimum threshold,thus achieving high and competitive *** outcome presented by the Classification model was analysed,and processed to create masks that will isolate the nuclei of these cells by applying OTSU algorithm,where the samples will be transferred from the original RGB colour space into HSV colour space,finding the optimal threshold values and computed by the Otsu algorithm,translating these im ages into monochrome *** nuclei-isolated cancerous samples were labelled and went through a set of Data Augmentation algorithms for expanding this new dataset and improving its quality,to be then then fed into a YOLOV5 model in order to detect if any Carcinomatous Pattern are present inside of the cancerous cell *** the end,this paper verified the effectiveness of combining the previously mentioned techniques with the presented models from a subjective and objectiv