Keupayaan pengurangan kebisingan konkrit berliang menggunakan cangkerang kelapa sawit sebagai gantian agregat bagi pembinaan penghalang kebisingan lebuh raya

Porous concrete is generally applied in noise barrier porous medium. Currently standard porous concrete has relatively low noise reduction and this will cause noise annoyance to resident and road users. This study aims to increase the noise reduction of noise barrier surface by replacing the natural aggregate with oil palm shell (OPS). The OPS is selected due high porosity characteristic and abundantly available. The objectives of the study are to determine the density, porosity, compressive strength and noise reduction capability of specimens and to evaluate the relationship between percentage of oil palm shell as aggregate replacement with strength and noise reduction capability. Specimens with mixture proportion of 25%, 50%, 75% and 100% aggregate replacement were carried out with specimen of porous concrete without OPS replacement as control specimen. The results showed porosity content significantly escalated with the increase of OPS while the density become lesser. Consequently, compressive strength decreased as the content of OPS increased, due to escalated porosity. Except 75% OPS and 100% OPS, however the values obtained were still within the typical range (2–28 N/mm2). OPS replacement showed better noise reduction coefficient but there is no clear relationship between noise reduction and percentage of OPS replacement. In respect with the compressive strength limit for noise barrier porous surface (2 N/mm2), the highest noise reduction is given by the 25% OPS replacement with compressive strength of 3.07 N/mm2. This could be due to the microstructure of OPS which increased the entrapped air inside the porous concrete. Thus, porous concrete with 25% OPS replacement can be potentially applied in porous medium of noise barrier

Breast cancer: imaging and radiotherapy with synchrotron radiation

The breast cancer is the most common cancer in woman worldwide. In this scenario, two aspects are very important: the early diagnosis and the efficacy of the care. The gold standard for the screening of breast cancer is the two-view mammography and the standard care includes surgery, usually coupled with chemotherapy or radiotherapy with 6-MV X-ray tangential beams from a linear accelerator. The problem of superimposition of tissue along the direction of the beam, which can make difficult the task of lesion detection in mammography, has led to the development of 3D techniques – such as Digital Breast Tomosynthesis (DBT) and Breast Computed Tomography (BCT) – which resolve the breast anatomy also in the longitudinal direction. In addition, in the last decades the use of phase-contrast (PhC) imaging techniques (which permit to detect the phase-shift of the X-ray beam in tissue) produced improvements in the detection of breast cancer. As regards adjuvant radiotherapy of breast cancer, an effective treatment has to guarantee the maximum sparing to the healty tissues, in particular to the skin. For this purpose, new techniques – such as IMRT, helical tomotherapy, VMAT – are under clinical investigation. Moreover, new kilovoltage rotational radiotherapy techniques with X-ray beam from orthovoltage X-ray tube as well as linear accelerator have been proposed. In this work, we investigated the use of the synchrotron radiation (SR) for both low-dose phase-contrast breast computed tomography (PhC-BCT) and breast rotational radiotherapy, via Monte Carlo simulations and measurements. Experiments were conducted at three different synchrotron radiation facilities: ELETTRA (Trieste, Italy), ESRF (Granoble, France), Australian Synchrotron (Melbourne, Australia). Phase contrast mammography on a cohort of patients was pioneered at ELETTRA in the last decade, showing the advantage of propagation based PhC imaging in producing higher conspicuity of breast masses; the ongoing projects at ELETTRA aim at devising a setup and a protocol for future computed tomography (CT) scans of the breast. The first part of the work, carried out in the framework of the SYRMA-CT/3D projects funded by INFN (National Institute for Nuclear Physics, Italy), showed the dosimetry measurements as well as the first imaging test of PhC-BCT at ELETTRA, carried out at 38 keV or lower energies. New dose metrics were introduced to take into account the partial breast irradiation envisaged for the exam; in addition, we carried out a characterization of dosimeters (TLD GR-200A and radiochromic film XR-QA2) to be employed for beam and phantom dosimetry. Finally, we showed the results of the first imaging test with a breast tissue specimen.In the second part of this PhD work, we demonstrated the feasibility of rotational breast radiotherapy with synchrotron radiation laying the foundations for the study of a new image-guided radiotherapy technique for breast cancer. This technique employs the same setup used for BCT but uses higher energies (60–120 keV) and higher intensity SR beams. The use of such low photon energies (with respect to megavoltage photon energies used in conventional radiotherapy) would provide a higher dose-enhancement when a radiosensitizing (e.g. gold nanoparticles) is used for breast radiotherapy. Possible applications of this technique could be the treatment of the small lesion and hypo-fractionated radiotherapy

Deep Learning in Medical Image Analysis

The accelerating power of deep learning in diagnosing diseases will empower physicians and speed up decision making in clinical environments. Applications of modern medical instruments and digitalization of medical care have generated enormous amounts of medical images in recent years. In this big data arena, new deep learning methods and computational models for efficient data processing, analysis, and modeling of the generated data are crucially important for clinical applications and understanding the underlying biological process. This book presents and highlights novel algorithms, architectures, techniques, and applications of deep learning for medical image analysis

Estimation of appropriate breast compression for robotized mammographic imaging

The paper discusses a doppler ultrasound system for breast stiffening estimation during breast compression in mammographic screening procedures developed using automatic (robotized) mammography units. These units can be considered robots as they are automated, instruct the patient and supervise that the procedure develops correctly. The paper addresses the problem, for the robotized mammographer, to determine automatically the amount of compression of the breast to ensure proper imaging while limiting the pain for the patient to the minimum inevitable. This is one of the key issues to solve to make robotic mammographers. The physical principle used is sonoelastography in a doppler arrangement. Two algorithms have been developed able to detect vibrational displacement of breast tissue by processing the echo signals. From the displacement and phase of the vibrating tissue, the value of the elastic modulus of the breast tissue can be derived and hence its strain value in the region of interest