The invention provides a method and device for constructing a 3D UNet network model for tumor detection, and a computer-readable storage medium. The method comprises: acquiring an LIDC data set from a medical image database, wherein the LIDC data set comprises a tumor CT image and a tumor region annotation in an xml format; converting the tumor region annotation in the xml format into a tumor region annotation in a mask format; dividing the converted LIDC data set into a training data set and a verification data set; preprocessing the training data set and the verification data set, and normalizing pixel values of the tumor CT image; constructing a 3D Unet network model on the basis of a keras framework; using the training data set to train the 3D Unet network model so as to acquire a weight of the 3D Unet network model; and using the verification data set to verify the validity of the 3D Unet network model. In the invention, a 3D Unet network is constructed, thereby quickly and accurately detecting a tumor focus region, and improving the efficiency and accuracy of tumor detection.
METHOD AND DEVICE FOR CONSTRUCTING 3D UNET NETWORK MODEL FOR TUMOR DETECTION, AND STORAGE MEDIUM