4:40 PM - 5:00 PM
[2N4-J-13-05] Lesion Detection in Computed Tomography Images using YOLOv3 and Domain Knowledge
Keywords:CNN, CT images, YOLOv3, Lesion Detection
In the field of image analysis, convolutional neural networks (CNN) have been successful. It is also applied in medical image analysis and includes skin visible images, X-ray images, computed tomography (CT) images, magnetic resonance images (MRI), etc.
In this research, we used You Only Look Once version 3 (YOLOv3), one of the latest deep - layer object detection methods, to detect the lesion site and to improve the precision of the previous study for the purpose of using in the medical field. As the verification data, the DeepLesion dataset used in the previous study was used and YOLOv3 was adapted to the chest image in the DeepLesion dataset. A model was created for each CT value used in actual medical practice, and a FROC curve exceeding that of the previous study was obtained. That is, we report reduction of false positive number per sensitivity.
In addition, with reference to the fact that the radiologist uses 3D information to identify lesions that are similar to normal tissues, we also report on model modification efforts using neighboring slices of CT images labeled with lesion sites in Deep Lesion.
In this research, we used You Only Look Once version 3 (YOLOv3), one of the latest deep - layer object detection methods, to detect the lesion site and to improve the precision of the previous study for the purpose of using in the medical field. As the verification data, the DeepLesion dataset used in the previous study was used and YOLOv3 was adapted to the chest image in the DeepLesion dataset. A model was created for each CT value used in actual medical practice, and a FROC curve exceeding that of the previous study was obtained. That is, we report reduction of false positive number per sensitivity.
In addition, with reference to the fact that the radiologist uses 3D information to identify lesions that are similar to normal tissues, we also report on model modification efforts using neighboring slices of CT images labeled with lesion sites in Deep Lesion.