US 11,684,333 B2 · Medical image analyzing system and method thereof

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.

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Claims26

Dependent claims

A medical image analyzing system, comprising:

an image preprocessing module, executed by a processor, configured to process at least one image corresponding to an organ to generate at least one processed image, wherein the processed image comprises a segmentation label corresponding to a cancerous part of the organ;
a patch cropping module, executed by the processor, configured to acquire a plurality of image patches from the processed image;
a feature analysis module, executed by the processor, configured to perform feature analysis on the plurality of image patches to obtain a plurality of feature values corresponding to each of the plurality of image patches;
a training module, executed by the processor, configured to train a full model using the plurality of feature values of each of the plurality of image patches to obtain a plurality of first prediction values corresponding to the respective plurality of image patches;
a threshold selection module, executed by the processor, configured to plot a first curve based on the plurality of first prediction values and determine a first threshold that is used for determining whether each of the plurality of image patches is cancerous according to the first curve;
and
a computer-assisted detection/diagnosis module, executed by the processor, configured to input at least one patient image to the image preprocessing module and the patch cropping module to generate a plurality of patient image patches and input the plurality of patient image patches into the full model to obtain a plurality of first prediction values corresponding to the respective plurality of patient image patches,
wherein the computer-assisted detection/diagnosis module further enables the threshold selection module to calculate at least one second prediction value corresponding to the at least one patient image based on the plurality of first prediction values respectively corresponding to the plurality of patient image patches, and plot a second curve based on the at least one second prediction value to determine a second threshold that is used for determining whether the at least one patient image is cancerous according to the second curve.

5 more elements

A medical image analyzing method, comprising:

processing at least one image corresponding to an organ to generate at least one processed image, wherein the processed image comprises a segmentation label corresponding to a cancerous part of the organ;
acquiring a plurality of image patches from the processed image;
performing feature analysis on the plurality of image patches to obtain a plurality of feature values corresponding to each of the plurality of image patches;
training a full model using the plurality of feature values of each of the plurality of image patches to obtain a plurality of first prediction values corresponding to the respective plurality of image patches;
plotting a first curve based on the plurality of first prediction values and determining a first threshold that is used for determining whether each of the plurality of image patches is cancerous according to the first curve;
inputting at least one patient image to generate a plurality of patient image patches;
inputting the plurality of patient image patches into the full model to obtain a plurality of first prediction values corresponding to the respective plurality of patient image patches;
calculating at least one second prediction value respectively corresponding to the at least one patient image based on the plurality of first prediction values respectively corresponding to the plurality of patient image patches;
and
plotting a second curve based on the at least one second prediction value to determine a second threshold that is used for determining whether the at least one patient image is cancerous according to the second curve.

7 more elements

Dependencies are inferred from the claim text.

Description9,034 words

Summary1,461 words

#The present disclosure relates to an image analyzing system and a method thereof, particularly to a medical image analyzing system and a method thereof.

#In current medical standards, pancreatic cancer is one of the cancers that are difficult to detect early, in which the survival rate drops significantly once tumor size exceeds 2 cm. In the existing technology, computed tomography (CT) imaging is currently the main method for detecting and evaluating pancreatic cancer. However, the detection efficiency of CT imaging still depends on the expertise/experience of the radiologist. For example, approximately 40% of the tumors smaller than 2 cm have been shown to evade detection by radiologist interpretation. This reflects that human image reading and interpretation of CT imaging is interpreter-dependent and prone to errors.

#Therefore, it has become an urgent issue in the art on how to provide a medical image analyzing system and a method thereof with improved detection rate applicable to, for example, identifying pancreatic cancer.

Brief description of the drawings9 figures

#FIG. 1A is a schematic diagram illustrating a first embodiment of a medical image analyzing system according to the present disclosure;

#FIG. 1B is a schematic diagram illustrating a second embodiment of the medical image analyzing system according to the present disclosure;

#FIG. 1C is a schematic diagram illustrating a third embodiment of the medical image analyzing system according to the present disclosure;

Detailed description7,375 words

#The following describes the implementation of the present disclosure by embodiments, and those skilled in the art can easily understand other advantages and effects of the present disclosure based on the contents disclosed in this specification, or implement or apply the present disclosure based on other different specific embodiments.

#FIG. 1A is a schematic diagram illustrating a first embodiment of a medical image analyzing system according to the present disclosure. The medical image analyzing system 1 may comprise a medical image analysis device 11 and a computer device 12 electrically connected to the medical image analysis device 11, wherein the medical image analysis device 11 and the computer device 12 communicate with each other through a wired or wireless network 13.

#The medical image analysis device 11 comprises an image preprocessing module 111, a patch cropping module 112, a feature analysis module 113, a training module 114 and a threshold selection module 115, and further comprises a processing unit 116, a communication unit 117 and a storage unit 118, of which the communication unit 117 and the storage unit 118 are coupled to the processing unit 116. In addition, the medical image analysis device 11 may be, for example, a mobile phone, a tablet computer, a notebook computer, a desktop computer, a server or a cloud server, of which the present disclosure is not limited thereto. Moreover, the medical image analysis device 11 may further comprise a display unit, such as a screen or a monitor (not shown).

Facts

Application

17/137,647Filed 30 Dec 2020 · us provisional application

Priority

TW 1091434559 Dec 2020

Published

US 2021/0204898 A18 Jul 2021

Granted

27 Jun 2023

Term ends

4 Sep 2041

Estimated · how

20 years from earliest known nonprovisional domestic filing plus recorded patent term adjustment, including 248 days of adjustment. Maintenance-fee lapses, terminal disclaimers and statutory extensions have not been checked. The continuity chain may be incomplete; this is not an enforceability determination.

Classification23 codes

A61B 6/5217
Involving processing of medical diagnostic data: extracting a diagnostic or physiological parameter from medical diagnostic data
G06T 7/0012
Inspection of images, e.g. flaw detection: biomedical image inspection
G06T 7/11
Segmentation; Edge detection: region-based segmentation
G06T 7/41
Analysis of texture: based on statistical description of texture

Timeline

3 Jan 2020Priority claimedTW 109143455
30 Dec 2020Application filedUS 17/137,647
30 Dec 2020Assigned to National Taiwan Universityassignment of assignor's interest
8 Jul 2021PublishedUS 2021/0204898 A1
27 Jun 2023GrantedUS 11,684,333 B2
12 Oct 2026TodayWithin its term
4 Sep 2041Term endsEstimated, includes 248 days of adjustment

Medical image analyzing system and method thereof

Life of this patent

Medical image analyzing system and method thereof

Life of this patent

Life of this patent

Abstract

Drawings

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Claims26

Description9,034 words

Drawings

Classification23 codes

Life of this patent

Description9,034 words