公开(公告)号：US20250148595A1

公开(公告)日：2025-05-08

申请号：US18932383

申请日：2024-10-30

Applicant: National Taiwan University ,  National Taiwan University Hospital

Inventor： Wei-Chung Wang ,  Wei-Chih Liao ,  Po-Ting Chen ,  Da-Wei Chang ,  Yen-Jia Chen ,  Yan-Chen Yeh ,  Po-Chuan Wang

IPC: G06T7/00 ,  G06V10/44

Abstract: A medical image analysis system comprises: a database for storing a first medical image data indicating a target medical image; and a server for accessing the database. The server includes: a first analysis module for generating a first determination data according to the first medical image data; a second analysis module for generating a second determination data according to the first medical image data; and an ensemble module communicatively connected with the first and second analysis modules and generating a third determination data according to the first and second determination data. The first and second determination data each indicate whether the target medical image includes a cancerous tissue image or indicate a chance of the target medical image including a cancerous tissue image. The third determination data indicates whether the target medical image includes a cancerous tissue image.

公开(公告)号：US11684333B2

公开(公告)日：2023-06-27

申请号：US17137647

申请日：2020-12-30

Applicant: National Taiwan University

Inventor： Wei-Chih Liao ,  Wei-Chung Wang ,  Kao-Lang Liu ,  Po-Ting Chen ,  Da-Wei Chang

IPC: A61B6/00 ,  G06T7/11 ,  G06T7/00 ,  G16H30/40 ,  G16H50/20 ,  A61B6/03 ,  A61B5/055

CPC classification number: A61B6/5217 ,  G06T7/0012 ,  G06T7/11 ,  G16H30/40 ,  G16H50/20 ,  A61B5/055 ,  A61B6/032 ,  G06T2207/10081 ,  G06T2207/10088 ,  G06T2207/20081 ,  G06T2207/20132 ,  G06T2207/30096

Abstract: Provided is a medical image analyzing system and a method thereof, which includes: acquiring a processed image having a segmentation label corresponding to a cancerous part of an organ (if present), generating a plurality of image patches therefrom, performing feature analysis on the image patches and model training to obtain prediction values, drawing a receiver operating characteristic curve using the prediction values, and determining a threshold with which determines whether the image patches are cancerous, so as to effectively improve the detection rate of, for example, pancreatic cancer.

公开(公告)号：US20210204898A1

公开(公告)日：2021-07-08

申请号：US17137647

申请日：2020-12-30

Applicant: National Taiwan University

Inventor： Wei-Chih Liao ,  Wei-Chung Wang ,  Kao-Lang Liu ,  Po-Ting Chen ,  Da-Wei Chang

IPC: A61B6/00 ,  G06T7/11 ,  G06T7/00 ,  G16H30/40 ,  G16H50/20

Abstract: Provided is a medical image analyzing system and a method thereof, which includes: acquiring a processed image having a segmentation label corresponding to a cancerous part of an organ (if present), generating a plurality of image patches therefrom, performing feature analysis on the image patches and model training to obtain prediction values, drawing a receiver operating characteristic curve using the prediction values, and determining a threshold with which determines whether the image patches are cancerous, so as to effectively improve the detection rate of, for example, pancreatic cancer.

公开(公告)号：US12106473B2

公开(公告)日：2024-10-01

申请号：US17507949

申请日：2021-10-22

Applicant: National Taiwan University

Inventor： Wei-Chung Wang ,  Wei-Chih Liao ,  Kao-Lang Liu ,  Po-Ting Chen ,  Po-Chuan Wang ,  Da-Wei Chang

IPC: G06T7/00 ,  A61B5/00 ,  G06N3/08 ,  G06T7/70 ,  G06T7/73 ,  G06V10/774 ,  G06V10/776 ,  G06V10/82 ,  G16H30/20

CPC classification number: G06T7/0012 ,  A61B5/425 ,  A61B5/4887 ,  A61B5/726 ,  A61B5/7267 ,  G06N3/08 ,  G06T7/70 ,  G06T7/73 ,  G06V10/774 ,  G06V10/776 ,  G06V10/82 ,  G16H30/20 ,  G06T2207/20016 ,  G06T2207/20064 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30096 ,  G06T2207/30204 ,  G06V2201/031

Abstract: A medical image analyzing system and a medical image analyzing method are provided and include inputting at least one patient image into a first model of a neural network module to obtain a result having determined positions and ranges of an organ and a tumor of the patient image; inputting the result into a second model of a first analysis module and a third model of a second analysis module, respectively, to obtain at least one first prediction value and at least one second prediction value corresponding to the patient image; and outputting a determined result based on the first prediction value and the second prediction value. Further, processes between the first model, the second model and the third model can be automated, thereby improving identification rate of pancreatic cancer.

公开(公告)号：US20220156929A1

公开(公告)日：2022-05-19

申请号：US17507949

申请日：2021-10-22

Applicant: National Taiwan University

Inventor： Wei-Chung Wang ,  Wei-Chih Liao ,  Kao-Lang Liu ,  Po-Ting Chen ,  Po-Chuan Wang ,  Da-Wei Chang

IPC: G06T7/00 ,  G06T7/73 ,  G16H30/20 ,  A61B5/00

Abstract: A medical image analyzing system and a medical image analyzing method are provided and include inputting at least one patient image into a first model of a neural network module to obtain a result having determined positions and ranges of an organ and a tumor of the patient image; inputting the result into a second model of a first analysis module and a third model of a second analysis module, respectively, to obtain at least one first prediction value and at least one second prediction value corresponding to the patient image; and outputting a determined result based on the first prediction value and the second prediction value. Further, processes between the first model, the second model and the third model can be automated, thereby improving identification rate of pancreatic cancer.

公开(公告)号：US12067717B2

公开(公告)日：2024-08-20

申请号：US17507948

申请日：2021-10-22

Applicant: National Taiwan University

Inventor： Wei-Chung Wang ,  Wei-Chih Liao ,  Kao-Lang Liu ,  Po-Ting Chen ,  Po-Chuan Wang ,  Ting-Hui Wu

IPC: G06T7/00 ,  A61B5/00 ,  G06N3/08 ,  G06T7/70 ,  G06T7/73 ,  G06V10/774 ,  G06V10/776 ,  G06V10/82 ,  G16H30/20

CPC classification number: G06T7/0012 ,  A61B5/425 ,  A61B5/4887 ,  A61B5/726 ,  A61B5/7267 ,  G06N3/08 ,  G06T7/70 ,  G06T7/73 ,  G06V10/774 ,  G06V10/776 ,  G06V10/82 ,  G16H30/20 ,  G06T2207/20016 ,  G06T2207/20064 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30096 ,  G06T2207/30204 ,  G06V2201/031

Abstract: A medical image analyzing system and a medical image analyzing method are provided and include inputting at least one patient image into a first model of a first neural network module to obtain a result having determined positions and ranges of an organ and a tumor of the patient image; inputting the result into a plurality of second models of a second neural network module, respectively, to obtain a plurality of prediction values corresponding to each of the plurality of second models and a model number predicting having cancer in the plurality of prediction values; and outputting a determined result based on the model number predicting having cancer and a number threshold value. Further, processes between the first model and the second models can be automated, thereby improving identification rate of pancreatic cancer.

公开(公告)号：US20220130038A1

公开(公告)日：2022-04-28

申请号：US17507948

申请日：2021-10-22

Applicant: National Taiwan University

Inventor： Wei-Chung Wang ,  Wei-Chih Liao ,  Kao-Lang Liu ,  Po-Ting Chen ,  Po-Chuan Wang ,  Ting-Hui Wu

IPC: G06T7/00 ,  G06T7/70 ,  G06V10/82 ,  G06V10/776 ,  G06V10/774 ,  G16H30/20 ,  G06N3/08 ,  A61B5/00

Abstract: A medical image analyzing system and a medical image analyzing method are provided and include inputting at least one patient image into a first model of a first neural network module to obtain a result having determined positions and ranges of an organ and a tumor of the patient image; inputting the result into a plurality of second models of a second neural network module, respectively, to obtain a plurality of prediction values corresponding to each of the plurality of second models and a model number predicting having cancer in the plurality of prediction values; and outputting a determined result based on the model number predicting having cancer and a number threshold value. Further, processes between the first model and the second models can be automated, thereby improving identification rate of pancreatic cancer.

公开(公告)号：US11424021B2

公开(公告)日：2022-08-23

申请号：US16868742

申请日：2020-05-07

Applicant: National Taiwan University

Inventor： Wei-Chih Liao ,  Wei-Chung Wang ,  Kao-Lang Liu ,  Po-Ting Chen ,  Ting-Hui Wu ,  Holger Roth

IPC: G06K9/00 ,  G16H30/40 ,  G16H50/20 ,  G06T7/00 ,  G06N3/08 ,  G06T7/11

Abstract: Provided are a medical image analyzing system and a method thereof, which mainly crop a plurality of image patches from a processed image including a segmentation label corresponding to a location of an organ, train a deep learning model with the image patches to obtain prediction values, and plot a receiver operating characteristic curve to determine a threshold which determines whether the image patches are cancerous, thereby effectively improving the detection rate of cancer.