Adaptive Electric Current Computed Tomography System
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
{'SignBlockName': 'name not available', 'PO_EMAI': None, 'PO_PHON': None}
This proposal seeks to continue the design, construction, and                   testing of a prototype electric current computed tomography                     (EECT) system.  This system applies patterns of electric current                through an array of electrodes on the surface of a body, and                    records the voltages that result on those electrodes.  From these               measured voltages the system generates and displays an                          approximate reconstruction of the electrical conductivity within                the body.  In order to achieve the theoretically predicted                      maximum signal-to-noise ratio, this system is adaptive in the                   sense that the successive patterns of current applied to the body               are determined from the previous voltage measurements and the                   optimization-reconstruction algorithm.                                                                                                                          The immediate impact of this proposed research on engineering and               medical imaging will be the demonstration that an adaptive system               can be built and made to yield image constructions that achieve                 the resolution predicted by the PI's theory.  The long term                     impact will be the creation of higher resolution impedance                      imaging systems than are possible with existing processes.                      Higher resolution systems will yield more powerful diagnostic                   tools in medicine, as well as more useful imaging techniques in                 nondestructive testing, geophysical exploration, and flow through               porous media.
{'FirstName': 'David', 'LastName': 'Isaacson', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David Isaacson', 'EmailAddress': 'isaacd@rpi.edu', 'NSF_ID': '000153536', 'StartDate': '05/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Rensselaer Polytechnic Institute', 'CityName': 'TROY', 'ZipCode': '121803590', 'PhoneNumber': '5182766000', 'StreetAddress': '110 8TH ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '20', 'CONGRESS_DISTRICT_ORG': 'NY20', 'ORG_UEI_NUM': 'U5WBFKEBLMX3', 'ORG_LGL_BUS_NAME': 'RENSSELAER POLYTECHNIC INSTITUTE', 'ORG_PRNT_UEI_NUM': None}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
[{'Code': '5345', 'Text': 'Engineering of Biomed Systems'}, {'Code': '9120', 'Text': 'CROSS-DIRECTORATE PROGRAMS'}]
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8706340.xml'}