Patent ID: 11900592
Assignee: PING AN TECHNOLOGY (SHENZHEN) CO., LTD
Field: Medical technology (Instruments)
Classification: CPC G  A | IPC A  G

Claim 11:
12. A device for pancreatic mass diagnosis and patient management, comprising:
a memory storing a computer program; and
a processor configured to execute the computer program stored in the memory to:
receive computed tomography (CT) images of a pancreas of a patient during a multi-phase CT scan, the CT images including a plurality of three-dimensional (3D) images of the pancreas for each phase of the multiple phases and the pancreas of the patient including a mass;
perform a segmentation process on the CT images of the pancreas and the mass to obtain a segmentation mask of the pancreas the mass of the patient, wherein the processor is further configured to:
concatenate the CT images of the pancreas of the patient to form a four-dimensional (4D) input X, wherein X∈RN×W×H×D, wherein R represents a matrix, W is an image width, H is an image height, D is an image depth, the multi-phase CT scan is an N-phase CT scan, and N is a positive integer,
feed the 4D input X into a segmentation network trained on an input Y which is one-hot encoded by combining a pancreas dataset with masses of radiologist-segmented pancreatic ductal adenocarcinoma (PDAC) and radiologist-segmented non-PDAC, to obtain the segmentation mask of the pancreas, wherein Y∈RK×W×H×D, K is a task label indicating a task including a classification task between the masses of the PDAC and the non-PDAC, and a treatment recommendation task, the segmentation network includes an nnUNet as a backbone network and a pixel-level segmentation loss function Lseg,, L
      
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F(x) is a softmax output of the nnUNet, and F(x)∈RK×W×H×D;
perform a mask-to-mesh process on the segmentation mask of the pancreas of the patient to obtain a mesh model including 156 vertices of the pancreas of the patient;
perform a classification process on the mesh model of the pancreas of the patient to identify a type and a grade of a segmented pancreatic mass; and
output updated CT images of the pancreas of the patient, the updated CT images including the segmented pancreatic mass highlighted thereon and the type and the grade of the segmented pancreatic mass annotated thereon.