Data processing for super-resolution ultrasound image enhancement
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Date
2023-10-30
Authors
Ρεβύθη, Μαρία
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Abstract
Recent research studies have revealed a significant surge in various cancer
types, with causes attributed to factors like air pollution, unhealthy diets and
modern lifestyles. Among these cancers, prostate cancer stands out as a critical
concern for men due to its high mortality rate when not detected early. Prostate
cancer diagnosis relies on the use of ultrasound waves. Ultrasound has gained
prominence as an imaging technique that can rival MRI in certain aspects, primarily
due to its cost-effectiveness, real-time imaging capabilities, portability, absence
of radiation effects, and user-friendly operation. However, it is worth noting that
its spatial resolution is relatively limited, often necessitating the use of MRI or
CT scans for precise assessments of soft tissue diseases.
CEUS has emerged as a solution to address this limitation by introducing
UCAs, which are non-linear sound wave scatterers. These agents, often referred
to as MBs, are injected into a specific region of the bloodstream that requires
examination. A specialized ultrasound transducer emits sound waves at a specific
frequency. These MBs act as robust scatterers of sound waves and, as a result,
reflect the transmitted signal. The reflected signal is then captured by the transducer
once more. This process relies on the piezoelectric effect found in certain materials,
meaning they can generate sound waves when subjected to an electric field, as
well as the reverse effect. Consequently, this approach allows for the creation
of high-contrast images.
SRUI allows for visualizing vascular architecture and dynamics at the level
of arterioles. This breakthrough offers exciting prospects in the field of cancer
detection and localization, providing invaluable insights into the intricate details
of the vascular network. Given the well-established correlation between micro-
vascularity and cancer progression, it becomes paramount to generate US images
capable of furnishing clinicians with information about the vascular system and
potentially identifying tumor growth at its early or more advanced stages.
Following the detection of these MBs in super-resolution images, the subsequent
step involves a tracking process. Typically, a sequential series of contrast-enhanced
images of the prostate is available, and the MBs, which are detected using localization
techniques, need to be linked across these consecutive frames. This linkage
allows for the creation of tracks for each MB, thereby revealing the pathways
through which these MBs traverse within the vessels.
The primary objective of this study is to enhance image quality, and this can
be achieved by improving both the detection and tracking parts of the algorithm.
The enhancement in the detection part involves the utilization of an automated
approach to determine the optimal BA instead of relying on manual adjustments.
In the tracking part, improvements are made by incorporating path smoothing
and fixed thresholds for CV and PD as a rejection criterion. The evaluation
process has been conducted both in synthetic and human prostate data.
Description
Keywords
Ultrasound, Prostate cancer, Image processing