Early detection of breast cancer is diagnosed using mammography, the gold standard in breast screening. However, its increased use also provokes radiation-induced breast malignancy. Thus, monitoring and regulating the mean glandular dose (MGD) is essential. The purpose of this study was to determine MGD for full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT) in the radiology department of a single centre. We also analysed the exposure factors as a function of breast thickness. A total of 436 patients underwent both FFDM and DBT. MGD was auto calculated by the mammographic machine for each projection. Patients’ data included compressed breast thickness (CBT), peak kilovoltage (kVp), milliampere-seconds (mAs) and MGD (mGy). Result analysis showed that there is a significant difference in MGD between the two systems, namely FFDM and DBT. However, the MGD values in our centre were comparable to other centres, as well as the European guideline (<2.5 mGy) for a standard breast. Although DBT improves the clinical outcome and quality of diagnosis, the risk of radiation-induced carcinogenesis should not be neglected. Regular quality control testing on mammography equipment must be performed for dose monitoring in women following a screening mammography in the future.

According to Breast Cancer Institute (BCI), Breast cancer is one of the most dangerous types of cancer that affects women all around the world. Based on clinical guidelines, the use of mammogram for an early detection of this cancer is an important step in reducing its danger. Thus, computer aided detection using image processing techniques in analyzing mammogram images and localizing abnormalities such as mass has been used. A False Positive (FP) rate is considered a challenge in localizing mass in mammogram images. Hence, in this paper, the rejection model based on the Support Vector Machine (SVM) has been used in reducing the FP rate of segmented mammogram images using the Chan-Vese method, initialized by the Marker Controller Watershed (MCWS) algorithm. Firstly, a mammogram image is segmented using the MCWS algorithm. Then, the segmentation is refined using Chan-Vese. After that, the SVM rejection model is built and is used in rejecting the non-correct segmented nodules. The dataset which consists of 16 nodules and 28 non-nodules has been obtained from the UKM Medical Centre. The experiment has shown the effectiveness of the SVM rejection model in reducing the FP rate compared to the result without the use of the SVM rejection model.

This chapter discusses radio-pathological correlation with recent imaging advances such as machine learning (ML) with the use of technical methods such as mammography and histopathology. Although criteria for diagnostic categories for radiology and pathology are well established, manual detection and grading, respectively, are tedious and subjective processes and thus suffer from inter-observer and intra-observer variations. Two most popular techniques that use ML, computer aided detection (CADe) and computer aided diagnosis (CADx), are presented. CADe is a rejection model based on SVM algorithm which is used to reduce the False Positive (FP) of the output of the Chan-Vese segmentation algorithm that was initialized by the marker controller watershed (MCWS) algorithm. CADx method applies the ensemble framework, consisting of four-base SVM (RBF) classifiers, where each base classifier is a specialist and is trained to use the selected features of a particular tissue component. In general, both proposed methods offer alternative decision-making ability and are able to assist the medical expert in giving second opinion on more precise nodule detection. Hence, it reduces FP rate that causes over segmentation and improves the performance for detection and diagnosis of the breast cancer and is able to create a platform that integrates diagnostic reporting system.

As an emerging technology, UltraWide Band (UWB) wireless communications provides a very different approach to the antenna technology compared to narrow band systems, which has been a very attractive choice for medical antenna development. In this paper presents the design and simulation of a hexagonal microstrip antenna along with a breast phantom simulation. The antenna is simulated by introducing a hexagon slot in the center of the patch an impedance bandwidth nearly 5 GHz is achieved. The presented antenna has been designed and simulated successfully. The simulation analysis of designed antenna is carried out using HFSS software. The obtained results with this antenna make it a suitable antenna for UWB systems and portable applications.

BackgroundAltered motor patterns of the local muscle system (LS) and global muscle system (GS) is reported among low back pain patients. However, the pattern of changes in the LS and GS among individuals with sacroiliac joint dysfunction (SJD) is not clear.ObjectiveThis study aimed to investigate the changes in the resting muscle thickness of LS and GS in SJD.MethodsA total of 40 individuals (20 participants with SJD and 20 healthy participants as matched controls) participated in this study. The resting thickness of the LS and GS such as rectus abdominis (RA), external oblique (EO), internal oblique (IO), transverses abdominis (TrA), and lumbar multifidus (LM) was measured using real time ultrasonography and the data were compared between the ipsilateral side and contralateral side among participants with SJD as well as healthy participants. Parametric and nonparametric statistics were used to analyse the data as appropriate.ResultsThe results showed that EO and IO were significantly reduced among SJD participants when compared with the contralateral side. Similarly, EO and LM were significantly reduced among the SJD group when compared with the controls.ConclusionThe findings of the study support a trend of reduced size in the resting thickness of the LS and GS in SJD