Development of an Expert Microscope System for 3-D Mapping  of Neurons
{'Code': '08080102', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'DBI', 'LongName': 'Div Of Biological Infrastructure'}}
{'SignBlockName': 'Machi F. Dilworth', 'PO_EMAI': None, 'PO_PHON': None}
This project will develop a neuron-tracking microscope system                   that utilizes built in knowledge of neuronal morphology to                      perform three-dimensional neuron tracing with minimal human                     assistance.  It will be accomplished by integrating newly                       created expert system and computer vision software with a                       computer driven video light microscope. The software will be                    designed for an existing Zeiss - Sun 3/160C video imaging                       computer microscope system.  The expert microscopy system (EMS)                 will acquire a depth sequence of images of the neuron and its                   neighborhood. The sequence will include all of the neuron's                     branching structure.  The EMS will analyze the images, treating                 them just as the human would treat the ordinary visual images                   he obtains while tracing the same neuron.  Human assistance                     will be called upon at the outset of data acquisition in order                  to guide the system to the neuron in question, and then later                   only if the system is incapable of making a reliable decision                   based upon its existing knowledge base.  The system will                        produce 3-D neuronal maps containing all the structural data                    of interest.  These will permit computer graphic                                reconstructions (including dynamic rotations) as well as                        numerical morphometric analyses.  They will also permit spatial                 analyses of populations of neurons. The EMS is intended to be                   capable of performing at least as well as a trained human using                 the same knowledge base.  The software will be designed to be                   device independent and therefore transportable to other imaging                 systems.  It will also be applicable to the new high                            resolution scanning confocal microscopes.                                                                                                                       The architectural organization of the nervous system is highly                  complex, with one nerve cell making numerous interconnections                   with other cells.  Presently, neuroscientists must mechanically                 trace the course of a neuron shown in microscopic images.  The                  software to be developed will automatically perform this task,                  saving substantial man-hours.  This capability will accelerate                  the acquisition of data to be analyzed for underlying patterns,                 leading to greater understanding of the relationship of                         structure to function.
{'FirstName': 'Edmund', 'LastName': 'Glaser', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Edmund M Glaser', 'EmailAddress': None, 'NSF_ID': '000167052', 'StartDate': '09/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Maryland at Baltimore', 'CityName': 'BALTIMORE', 'ZipCode': '212011531', 'PhoneNumber': '4107063559', 'StreetAddress': '220 ARCH ST OFC LEVEL2', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MD07', 'ORG_UEI_NUM': 'Z9CRZKD42ZT1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MARYLAND, BALTIMORE', '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': '1108', 'Text': 'INSTRUMENTAT & INSTRUMENT DEVP'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8811769.xml'}