Abstract: A malignant tumor with quick development and early metastatic dissemination is known as small-cell lung cancer (SCLC). Improved survival depends on early and accurate SCLC diagnosis. Accurate cancer segmentation helps medical professionals better comprehend the location and scope of cancers and make more accurate diagnoses. The YOLO framework is being utilized in this effort to both locate and categorize a lung tumor that is connected to the edge of blood vessels. The R-CNN methods presented in Part 1 mainly employ regions to localise objects within images. The network only looks at the areas ofthe image that are most likely to contain an item, not the complete picture. The biggest benefit of employing YOLO is how quick and precise it is.

Keywords: Convolutional Neural Network, Image Processing, Pooling, Median

| DOI: 10.17148/IARJSET.2023.10218