Improving segmentation and classification of renal tumors in small sample 3D CT images using transfer learning with convolutional neural networks.
Journal:
International journal of computer assisted radiology and surgery
Published Date:
Mar 15, 2022
Abstract
PURPOSE: Computed tomography (CT) images can display internal organs of patients and are particularly suitable for preoperative surgical diagnoses. The increasing demands for computer-aided systems in recent years have facilitated the development of many automated algorithms, especially deep convolutional neural networks, to segment organs and tumors or identify diseases from CT images. However, performances of some systems are highly affected by the amount of training data, while the sizes of medical image data sets, especially three-dimensional (3D) data sets, are usually small. This condition limits the application of deep learning.