National Taiwan University

Yuan Ze University

Ownway Biotronics Inc.

Wei-Chih Liao

Wei-Chung Wang

Po-Ting Chen

Kao-Lang Liu

Po-Chuan Wang

Ting-Hui Wu

Da-Wei Chang

Chi-Chia Chang

Pei-Yu Lin

Ran-Zan Wang

Shou-Hung Welkin Ling

Holger Roth

Wan-Chih Lin

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.

Medical image analyzing system for identifying pancreatic cancer using machine learning and method thereof

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.

Medical image analyzing system and method thereof

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.

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.

A method for generating a color QR code includes: generating a grayscale image according to a color image; providing a QR code and dividing the grayscale image into the number of grayscale image modules matching module numbers of the QR code; generating a threshold mask image from grayscale image modules; cutting out each center block from center part of each grayscale image module and calculating characteristics values of the center blocks; identifying color of each module of the QR code, and comparing the characteristics values of the center blocks of the grayscale image to the corresponding threshold value compensated by robustness value to identify center blocks needing pixel luminance adjustment; dividing the center blocks needing pixel luminance adjustment into multiple layers of blocks; adjusting pixel luminance of the multiple layers of blocks using the robustness value times with corresponding weightings; and generating a fused color QR code.

Method for generating color QR code

An electro-tactile panel (ETP) apparatus for a display panel is disclosed. The ETP apparatus is composed of three major parts: a controller, a panel, and a holder. The panel consists of four layer made of transparent material. The first layer is an insulating substrate, the second layer is a conductive layer formed of a plurality of horizontal electrodes on the first layer. The third layer is an insulating layer having holes formed therein, which corresponding to the electrodes on the second layer. The fourth layer is a conductive layer formed of a plurality of vertical electrodes on the third layer. The panel is attached to the display panel by means of the holder apparatus. The electro-tactile signal and cursor position is process by the controller when the skin touches the panel so that some positions of the vertical electrodes and horizontal electrodes are electrically connected through the holes.

Growing community of inventors

Taipei, Taiwan

Wei-Chih Liao