# US 7,492,938 B2 · Methods and systems for creating data samples for data analysis > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 7,492,938 B2 - Document ID: US7492938B2 - Status: Granted - Kind: B2 - Application number: 11/674,968 - Filed: 2007-02-14 - Published: 2007-08-23 - Granted: 2009-02-17 - Earliest claimed: 2006-02-14 - Assignees: Intelliscience Corporation - Inventors: Robert M. Brinson, Jr.; Nicholas Levi Middleton; William K. Naguszewski; Bryan Glenn Donaldson; Robert Leon Bass, II - Web page: https://patentgrep.com/patent/US7492938B2 ## CPC - G06T 7/0012: {Biomedical image inspection} - G06T 2207/30004: Biomedical image processing - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ## Abstract Systems and methods for creating data samples for data analysis. The method includes imaging at least a portion of a first object having a target portion to generate a first image, analyzing the first image by running a first series of algorithms using the first image to generate a first algorithm value cache, removing the target portion from the first object to form a modified first object, imaging at least a portion of the modified first object to generate a second image, analyzing the second image by running the first series of algorithms using the second image to generate a second algorithm value cache, generating a transformed result by running a subtraction process using the first algorithm value cache and the second algorithm value cache, and storing the transformed result in a knowledge base. ## Claims ### Claim 1 A method for training a knowledge base, the method comprising: imaging at least a portion of a first object having a target portion to generate a first image; analyzing the first image using a first series of algorithms to generate a first algorithm value cache; removing the target portion from the first object to form a modified first object; imaging at least a portion of the modified first object to generate a second image; analyzing the second image using the first series of algorithms to generate a second algorithm value cache; generating a transformed result using a subtraction process on the first algorithm value cache and the second algorithm value cache; and storing the transformed result in a knowledge base. ### Claim 2 (depends on 1) The method of claim 1, wherein the first object includes a cadaver and the target portion includes a diseased portion. ### Claim 3 (depends on 1) The method of claim 1, wherein the first object includes an agricultural product and the target portion includes a contaminant. ### Claim 4 (depends on 1) The method of claim 1, wherein analyzing the first image comprises: a) retrieving a first target data element in a data set corresponding to the first image; b) processing the first series of algorithms on a target data area for the retrieved first target data element; c) repeating a) and b) for a plurality of target data elements in the first data set; and d) storing the results of the processed first series of algorithms to generate the first algorithm value cache. ### Claim 5 (depends on 1) The method of claim 1, further comprising analyzing an unknown sample using the stored transformed result. ### Claim 6 A method for training a knowledge base, the method comprising: imaging a test object formed of a benchmark material to generate a first image; analyzing the first image using a first series of algorithms to generate a first algorithm value cache; placing the test object in a cadaver to form a cadaver and test object combination; imaging at least a portion of the cadaver and test object combination to generate a second image; analyzing the second image using the first series of algorithms to generate a second algorithm value cache; performing a subtraction process using the first and second algorithm value cache to generate a filter; receiving a tissue sample containing a tumor; imaging the tissue sample to generate a third image; analyzing the third image using the first series of algorithms to generate a third algorithm value cache; transforming the third algorithm value cache using the filter to generate a transformed result; and storing the transformed result in a knowledgebase. ### Claim 7 (depends on 6) The method of claim 6, further comprising removing any normal tissue from the tissue sample before imaging the tissue sample. ### Claim 8 (depends on 6) The method of claim 6, wherein the benchmark material includes stainless steel. ### Claim 9 (depends on 6) The method of claim 6, wherein the benchmark material includes titanium. ### Claim 10 (depends on 6) The method of claim 6, wherein imaging the test object and the tissue sample includes ultrasound imaging. ### Claim 11 (depends on 6) The method of claim 6, further comprising analyzing an unknown sample using the stored transformed result. ### Claim 12 A system for training a knowledge base comprising: a processor; a memory in data communication with the processor; a user interface in data communication with the processor; a software module for storage in the memory and operable by the processor, the software module configured to: generate a first algorithm value cache using a first series of algorithms and previously generated diseased cadaver image data; generate a second algorithm value cache using the first series of algorithms and previously generated cadaver with diseased portion removed image data; generate a transformed result using a subtraction process on the first algorithm value cache and the second algorithm value cache; and store the transformed result in a knowledgebase. ### Claim 13 (depends on 12) The system of claim 12, wherein the software module is further configured to analyze previously generated unknown sample image data using the transformed result. ### Claim 14 A system for training a knowledge base comprising: a processor; a memory in data communication with the processor; a user interface in data communication with the processor; and a software module for storage in the memory and operable by the processor, the software module configured to: generate a first algorithm value cache using a first series of algorithms and previously generated test object image data; generate a second algorithm value cache using the first series of algorithms and previously generated cadaver with test object image data; perform a subtraction process using the first algorithm value cache and the second algorithm value cache to generate a filter; generate a third algorithm value cache using the first series of algorithms using previously generated tissue sample image data; generate a transformed tissue sample result using the filter and the third algorithm value cache; and store the transformed result in a knowledgebase. ### Claim 15 (depends on 14) The system of claim 14, wherein the test object image data was generated using a test object made of a benchmark material that includes stainless steel. ### Claim 16 (depends on 14) The system of claim 14, wherein the test object image data was generated using a test object made of a benchmark material that includes titanium. ### Claim 17 (depends on 14) The system of claim 14, wherein the test object image data and the tissue sample image data include ultrasound image data. ### Claim 18 (depends on 14) The system of claim 14, wherein the software module is further configured to analyze previously generated unknown sample image data using the transformed result.