Difference between revisions of "Projects:GliomaSubtypeClassification"
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Glioma histologies are the primary factor in the prognostic estimates and are used in determining the proper course of treatment. Furthermore, due to the sensitivity of cranial environment, real-time tumor cell classification and boundary detection can aid in the precision and completeness of tumor resection. By a recent improvement in mass spectrometry that allows for data collection in ambient environments without preparation, the goal is to provide surgeons with histopathological information for a resected sample. | Glioma histologies are the primary factor in the prognostic estimates and are used in determining the proper course of treatment. Furthermore, due to the sensitivity of cranial environment, real-time tumor cell classification and boundary detection can aid in the precision and completeness of tumor resection. By a recent improvement in mass spectrometry that allows for data collection in ambient environments without preparation, the goal is to provide surgeons with histopathological information for a resected sample. | ||
| − | = Result = | + | == Result == |
| − | = Key Investigators = | + | == Key Investigators == |
Georgia Tech: Jacob Huang, Behnood Gholami, and Allen Tannenbaum | Georgia Tech: Jacob Huang, Behnood Gholami, and Allen Tannenbaum | ||
Revision as of 16:06, 4 April 2011
Home < Projects:GliomaSubtypeClassificationBack to Georgia Tech Algorithms
Glioma Subtype Classification from Mass Spectrometry Data
Description
Glioma histologies are the primary factor in the prognostic estimates and are used in determining the proper course of treatment. Furthermore, due to the sensitivity of cranial environment, real-time tumor cell classification and boundary detection can aid in the precision and completeness of tumor resection. By a recent improvement in mass spectrometry that allows for data collection in ambient environments without preparation, the goal is to provide surgeons with histopathological information for a resected sample.
Result
Key Investigators
Georgia Tech: Jacob Huang, Behnood Gholami, and Allen Tannenbaum
