SYSTEMS AND METHODS FOR EFFICIENT IMAGING

• US 20110028825A1
• Filed: 06/03/2010
• Published: 02/03/2011
• Est. Priority Date: 12/03/2007
• Status: Abandoned Application

• Current Assignee: Dataphysics Research Incorporated
• Original Assignee: Dataphysics Research Incorporated
• Inventors: WOLFE, Gene J., Schuster, James A., TSYPIN, Maxim M., ABHYANKAR, Vishwas G., RODER, Heinrich, DOUGLAS, Steven K., Riegel, Stephen
• Application Number:
  US12/793,468
• Publication Number:
  US 20110028825A1
• Time in Patent Office: Days
• US Class Current: 600/407
• CPC Class Codes: G06T 19/00 Manipulating 3D models or images for computer graphics
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 2210/41 Medical
• CPC Class Codes: G06T 2219/004 Annotating, labelling
• CPC Class Codes: G06T 2219/028 Multiple view windows (top-side-front-sagittal-orthogonal)
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A system and methods for more efficient review, processing, analysis and diagnoses of medical imaging data is disclosed. The system and methods include automatically segmenting and labeling imaging data by anatomical feature or structure. Additional tools that can improve the efficiency of health care providers are also disclosed.

Claims

1. A method for processing medical imaging data by a computer system, the method comprising:

acquiring a first corpus data set comprising a three-dimensional data set;

comparing reference database data to the three-dimensional data set;

automatically segmenting the three-dimensional data set, wherein segmenting comprises identifying and labeling anatomical features within the three-dimensional data set;

navigating through the three-dimensional data set;

annotating the three-dimensional data set;

generating an electronic file comprising inserting patient data in an electronic template and comprising automated detection diagnosing;

altering the electronic file comprising adding observations to the electronic file after generating the electronic file; and

transmitting the electronic file from a first computer system to a second computer system.

2. The method of claim 1, wherein comparing further comprises scaling the acquired first corpus data with respect to the reference database data.

3. The method of claim 2, wherein scaling comprises deforming processing more than one distinct deformation vector to deform the acquired first corpus data.

4. The method of claim 3, further comprising comparing the first corpus data set to a past corpus data set for the same patient.

5. The method of claim 4, further comprising tagging and/or highlighting data in the first corpus data set, wherein highlighting comprises comparing with the past corpus data set.

6. The method of claim 1, further comprising altering the opacity of a feature in the three-dimensional data set.

7. The method of claim 1, further comprising navigating through the two-dimensional data set.

8. The method of claim 1, further comprising the first computer transmitting the electronic file to a third computer over a network, wherein the electronic file comprises data edited for a user of the third computer.

9. The method of claim 1, wherein annotating comprises linking observational text data to the data set.

10. The method of claim 1, wherein generating the electronic file comprises executing an algorithm to increase diagnostic efficiency.

11. A method for displaying medical corpus data, the method comprising:

visually displaying at least one two-dimensional image concurrent with a three-dimensional volumetric image corresponding to the at least one two-dimensional image; and

visually displaying synchronous three-dimensional and two-dimensional navigation through the at least one two-dimensional image and the three-dimensional volumetric image.

12. The method of claim 11, further comprising:

acquiring a first set of three-dimensional data points, constructing the at least one two-dimensional image from at least some of the three-dimensional data points; and

constructing the three-dimensional volumetric image from at least some of the three-dimensional data points.

13. The method of claim 11, further comprising measuring a geometric measurement of a feature in the first three-dimensional volumetric image, and creating an electronic file comprising the measurement.

14. The method of claim 13, further comprising measuring a geometric measurement of the feature in one of the at least one two-dimensional images, and synchronously displaying the geometric dimension in the first three-dimensional volumetric image.

15. A method of diagnosing a patient using a first computer system comprising a radiological corpus data set, the method comprising:

segmenting the corpus data set based on tissue-specific parameters, wherein the segmented data set comprises tissue-identifying data;

wherein segmenting comprises automatically identifying a seed voxel in an anatomical feature in the data set, and linking a label of the anatomical feature to the location in the data set of the anatomical feature.

16. The method of claim 15, further comprising adjusting the transparency of the segmented data based on the tissue-identifying data.

17. The method of claim 15, wherein the tissue-identifying data comprises groups of organs.

18. The method of claim 15, wherein the corpus data comprises three-dimensional data, and wherein the method further comprises two-dimensional sectioning of the three-dimensional data.

19. The method of claim 15, further comprising logging within the data set actions taken with the data set.

20. The method of claim 15, wherein the corpus data set comprises a three-dimensional data set, and further comprising constructing a three-dimensional volume from the corpus data set, wherein the three-dimensional volume comprises voxels, and wherein the labeling comprises associating at least one of the voxels with the anatomical labels.