Efficient ultrasonic signal processing techniques for aided medical diagnostics

Ultrasound imaging is widely used in medical diagnostics as it is the fastest, least invasive, and least expensive imaging modality. However, ultrasound images are intrinsically difficult to be interpreted. In this scenario, Computer Aided Detection (CAD) systems can be used to support physicians during diagnosis providing them a second opinion. This thesis discusses efficient ultrasound processing techniques for computer aided medical diagnostics, focusing on two major topics: (i) Ultrasound Tissue Characterization (UTC), aimed at characterizing and differentiating between healthy and diseased tissue; (ii) Ultrasound Image Segmentation (UIS), aimed at detecting the boundaries of anatomical structures to automatically measure organ dimensions and compute clinically relevant functional indices. Research on UTC produced a CAD tool for Prostate Cancer detection to improve the biopsy protocol. In particular, this thesis contributes with: (i) the development of a robust classification system; (ii) the exploitation of parallel computing on GPU for real-time performance; (iii) the introduction of both an innovative Semi-Supervised Learning algorithm and a novel supervised/semi-supervised learning scheme for CAD system training that improve system performance reducing data collection effort and avoiding collected data wasting. The tool provides physicians a risk map highlighting suspect tissue areas, allowing them to perform a lesion-directed biopsy. Clinical validation demonstrated the system validity as a diagnostic support tool and its effectiveness at reducing the number of biopsy cores requested for an accurate diagnosis. For UIS the research developed a heart disease diagnostic tool based on Real-Time 3D Echocardiography. Thesis contributions to this application are: (i) the development of an automated GPU based level-set segmentation framework for 3D images; (ii) the application of this framework to the myocardium segmentation. Experimental results showed the high efficiency and flexibility of the proposed framework. Its effectiveness as a tool for quantitative analysis of 3D cardiac morphology and function was demonstrated through clinical validation.

Design and evaluation of aerosol and liquid separation systems

Conventional chromatographic columns are packed with porous beads by the universally employed slurry-packing method. The lack of precise control of the particle size distribution, shape and position inside the column have dramatic effects on the separation efficiency. In the first part the thesis an ordered, three-dimensional, pillar-array structure was designed by a CAD software. Several columns, characterized by different fluid distributors and bed length, were produced by a stereolithographic 3D printer and compared in terms of pressure drop and height equivalent to a theroretical plate (HETP). To prevent the release of unwanted substances and to provide a surface for immobilizing a ligand, pillars were coated with one or more of the following materials: titanium dioxide, nanofibrillated cellulose (NFC) and polystyrene. The external NFC layer was functionalized with Cibacron Blue and the dynamic binding capacity of the column was measured by performing three chromatographic cycles, using bovine serum albumin (BSA) as target molecule. The second part of the thesis deals with Covid-19 pandemic related research activities. In early 2020, due to the pandemic outbreak, surgical face masks became an essential non-pharmaceutical intervention to limit the spread. To address the consequent shortage and to support the reconversion of the Italian industry, in late March 2020 a multidisciplinary group of the University of Bologna created the first Italian laboratory able to perform all the tests required for the evaluation and certification of surgical masks. More than 1200 tests were performed on about 350 prototypes, according to the standard EN 14683:2019. The results were analyzed to define the best material properties and masks composition for the production of masks with excellent efficiency. To optimize the usage of surgical masks and to reduce their environmental burden, the variation of their performance over time of usage were investigated as to determine the maximum lifetime.