Susanna Marricchi
TOWARDS STANDARDIZED OPTIC NERVE SHEATH DIAMETER ASSESSMENT: AN INTEGRATED ANATOMY-AWARE DEEP LEARNING FRAMEWORK FOR TRANSORBITAL ULTRASONOGRAPHY.
Rel. Kristen Mariko Meiburger, Kai Riemer. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2026
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Abstract
Extending a Deep Ultrasound assessment of the optic nerve sheath diameter (ONSD) represents a promising non-invasive method for estimating intracranial pressure (ICP). However, its widespread use in clinical practice is limited by the marked operator-dependent variability that characterizes both the acquisition and measurement of ultrasound images. The presence of artifacts intrinsic to ultrasound imaging, such as speckle noise, acoustic shadows and partial volume artifacts, makes it difficult to identify the anatomical margins of the optic nerve sheath. Added to these challenges are the difficulties associated with analyzing dynamic ultrasound sequences and the ambiguity in identifying the anatomical landmarks required for the standardized measurement of the ONSD at 3 mm from the bulbar insertion.
The aim of this thesis is to develop a Deep Learning-based pipeline for the standardization and automation of the entire ONSD analysis process in transorbital ultrasound
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