Presentation2_on_Lung_Cancer_Detection.pptx

This is a presentation on Lung Cancer Detection.

1. Detection of Lung cancer from CT image using SVM classification and compare the survival rate of patients using 3D Convolutional neural network (3D CNN) on lung nodules data set.

2. Contents Abstract Existing System Drawbacks of Existing System Proposed System Advantages of Proposed System Literature Review Requirements Data Set

3. In this technological era, we are determined to computerize everything using Artificial intelligence and Machine Learning. The medical industry is no exception. As we previously had known the wonders of AI and data analytics technologies has done in the medical industry. In this project, we are pre-processing the medical picture or a CT scan image. The image is segmented and augmented into small pictures using the methods. Once, the region of interest(ROI) in the image is identified which is related to the lung cancer cell, the segmentation process proceeds to the next pixel of the CT image. The process includes – data gathering , data cleaning, segmentation, data analytics, and conclusion of the problem. The mentioned procedures are all based on the deep learning, CNN and image processing techniques.

4. CPU: A modern multi-core processor with at least 8 cores, such as an Intel i7 or AMD Ryzen 7. RAM: At least 8 GB of memory, preferably 64 GB or more, to handle large datasets and multi-tasking. GPU: A powerful graphics card with at least 8 GB of memory, preferably 11 GB or more, such as an NVIDIA RTX 3080 or higher, to accelerate deep learning computations. Storage: A fast solid-state drive (SSD) with at least 1 TB of capacity, preferably 2 TB or more, to store datasets and trained models.

5. Glimpses of India

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