Neural network based approach for anomaly detection in the lungs region by electrical impedance tomography

Physiological Measurement

Volumn 26, Issue 4, 2005, Pages 489-502

  Minhas, Atul S ^a   Reddy, M Ramasubba ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY MADRAS   (India)

Author keywords

Anomaly detection; Canonical current patterns; Conductivity; Impedance tomography; Neural networks; OLSA

Indexed keywords

BIOLOGICAL ORGANS; ELECTRIC IMPEDANCE; ELECTRIC IMPEDANCE MEASUREMENT; ELECTRIC IMPEDANCE TOMOGRAPHY;

ANOMALY DETECTION; CANONICAL CURRENT PATTERN; CLASSIFICATION ERRORS; CONDUCTIVITY; CURRENT PATTERNS; ELECTRICAL IMPE DANCE TOMOGRAPHY (EIT); IMPEDANCE TOMOGRAPHY; LUNG REGIONS; NEURAL-NETWORKS; OLSA;

RADIAL BASIS FUNCTION NETWORKS;

ANALYTICAL ERROR; ARTICLE; ARTIFICIAL NEURAL NETWORK; COMPUTER ASSISTED IMPEDANCE TOMOGRAPHY; COMPUTER SIMULATION; DIAGNOSTIC IMAGING; FINITE ELEMENT ANALYSIS; LUNG BLOOD FLOW; LUNG MALFORMATION; MATHEMATICAL MODEL; NON INVASIVE MEASUREMENT; PRIORITY JOURNAL; THORACIC CAVITY;

EID: 20044373471     PISSN: 09673334     EISSN: 09673334     Source Type: Journal    
DOI: 10.1088/0967-3334/26/4/014     Document Type: Article

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