Litcius/Paper detail

Automated Detection of Hydrocephalus in Pediatric Head Computed Tomography Using VGG 16 CNN Deep Learning Architecture and Based Automated Segmentation Workflow for Ventricular Volume Estimation

H. Sekkat, A. Khallouqi, Omar El Rhazouani, Abdellah Halimi

2025Journal of Imaging Informatics in Medicine5 citationsDOIOpen Access PDF

Topics & Concepts

WorkflowSegmentationHead (geology)Volume (thermodynamics)Artificial intelligenceComputed tomographyComputer scienceHydrocephalusDeep learningComputer visionPattern recognition (psychology)Nuclear medicineRadiologyMedicineGeologyPhysicsDatabaseGeomorphologyQuantum mechanicsAdvanced Neural Network ApplicationsBrain Tumor Detection and ClassificationCerebrospinal fluid and hydrocephalus
Automated Detection of Hydrocephalus in Pediatric Head Computed Tomography Using VGG 16 CNN Deep Learning Architecture and Based Automated Segmentation Workflow for Ventricular Volume Estimation | Litcius