Feature analysis for Parkinson’s disease detection based on transcranial sonography image

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7512 LNCS, Issue , 2012, Pages 272-279

  Chen, Lei ^a   Hagenah, Johann ^b   Mertins, Alfred ^a  

^a UNIVERSITY OF LÜBECK   (Germany)

^b UNIVERSITY HOSPITAL SCHLESWIG HOLSTEIN   (Germany)

Author keywords

Blob detection; Feature analysis; Local feature; Parkinson s disease; Transcranial sonography

Indexed keywords

DIAGNOSIS; IMAGE ANALYSIS; LARGE DATASET; MEDICAL COMPUTING; MEDICAL IMAGING; ULTRASONIC APPLICATIONS; ULTRASONOGRAPHY;

BLOB DETECTION; CLINICAL PRACTICES; FEATURE ANALYSIS; FEATURE SELECTION METHODS; IMAGE ANALYSIS METHOD; LOCAL FEATURE; TRANSCRANIAL SONOGRAPHY; ULTRASOUND MACHINES;

FEATURE EXTRACTION;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; DOPPLER ECHOGRAPHY; ECHOGRAPHY; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; PARKINSON DISEASE; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SUBSTANTIA NIGRA;

ALGORITHMS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; PARKINSON DISEASE; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBSTANTIA NIGRA; ULTRASONOGRAPHY, DOPPLER, TRANSCRANIAL;

MLCS; MLOWN;

EID: 84872916438     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33454-2_34     Document Type: Conference Paper

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