Delft Breast Ultrasound

The development of a water-cup ultrasound breast scanning system

Master thesis (2019)

Authors

E.B.G. Janssen Applied Sciences

Contributors

K.W.A. van Dongen (supervisor 1)
U. Taskin (supervisor 2)
Faculty
Applied Sciences
Copyright: © 2019 Ernest Janssen
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Published Date

13-03-2019

Language

English

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Faculty

Applied Sciences

Abstract

Breast cancer is impacting over 1.5 million women each year. Early detection is essential in decreasing the mortality rate. Mammography is currently the golden standard for breast screening. However, this method is not ideal and water-bath ultrasound breast scanning is considered to be a promising screening modality. This type of scanning system is able to obtain ultrasound reflection and transmission data. In this study, a water-cup breast scanning setup is built. The setup consists of a plastic cup with four acoustic windows and four phased array ultrasound probes. The water-cup is used to execute a phantom study. The phantom study gives insight into the operability of the built water-cup. The differences between reflection and transmission data are observed and utilised. One imaging algorithm and two inversion algorithms are employed to reconstruct an image of the phantom. The images of the different algorithms are compared.
Furthermore, a method is proposed that reduces the computation time of a reflection data based Born inversion algorithm. In the end, the water-cup is used to image an ex-vivo human breast. Finally, the limitations of the built water-cup are stated. In addition to manufacturing the water-cup, a pulse-echo-scan of an ex-vivo human breast is made. This pulse-echo-scan is compared with the cross-sectional photograph of the breast. Due to the pudding-like structure of the breast, it is challenging to make a cross-section at the same position as the pulse-echo-scan is made. The pulse-echo-scan is made at the Pathology Department of the Erasmus MC. The ex-vivo human breast study helps to understand what structures are present in the breast. This knowledge can be used to build a new measurement setup and optimize the imaging algorithms for finding tumours.