Computer aided diagnosis (CAD) is widely considered an important application of deep learning in healthcare. However, brain data with lesion location labels are rare in MRI domain. Recently, Microsoft Research has released a dataset of clinical pathology annotations based on the raw images from fastMRI and named it fastMRI+. Here, fastMRI+ brain dataset was analyzed and used to train deep learning-based models for lesion detection. Some well-known object detection architectures such as YOLOv3, Faster-RCNN and YOLOX were compared. Overall, this abstract established a baseline with improvement suggestions for future studies.