Analysis of MRI brain tumor images using deep learning techniques

A popular deep learning-based object detection technique is the 'You Only Look Once' v3 (YOLOv3) method for brain tumor detection from tumor patients. The YOLOv3 model was trained using a set of 3064 pre-processed and labeled T1-weighted contrast-enhanced (CE) MRI images. A strong set of features for brain tumor detection was generated using transfer learning and weights from the MSCOCO dataset that were pre-trained. A mean average precision of 94.14 percent, a precision of 91.34 percent, recall of 90.58%, and an F1-Score of 92.55% were obtained, overcoming previous YOLO detection approaches and research that used bounding box detection to accomplish the same job, such as Faster R-CNN. This is a significant achievement. YOLOv3-Tiny may detect brain tumor automatically at an early stage with the help of transfer learning, as shown in the conclusion. This research primarily serves to aid medical professionals in their efforts to detect brain tumors through the use of imaging techniques.