DISCUSSION: This paper presents comprehensive report on breast carcinoma disease and its modalities available for detection and diagnosis, as it delves into the screening and detection modalities with special focus placed on the non-invasive techniques and its recent advancement work done, as well as a proposal on a novel method for the application of early breast carcinoma detection.
CONCLUSION: This paper aims to serve as a foundation guidance for the reader to attain bird's eye understanding on breast carcinoma disease and its current non-invasive modalities.
DISCUSSION: It is a set of various methodologies which are used to capture internal or external images of the human body and organs for clinical and diagnosis needs to examine human form for various kind of ailments. Computationally intelligent machine learning techniques and their application in medical imaging can play a significant role in expediting the diagnosis process and making it more precise.
CONCLUSION: This review presents an up-to-date coverage about research topics which include recent literature in the areas of MRI imaging, comparison with other modalities, noise in MRI and machine learning techniques to remove the noise.
METHODS: Such activity is recorded through various neuroimaging techniques like fMRI, EEG, MEG etc. EEG signals based localization is termed as EEG source localization. The source localization problem is defined by two complementary problems; the forward problem and the inverse problem. The forward problem involves the modeling how the electromagnetic sources cause measurement in sensor space, while the inverse problem refers to the estimation of the sources (causes) from observed data (consequences). Usually, this inverse problem is ill-posed. In other words, there are many solutions to the inverse problem that explains the same data. This ill-posed problem can be finessed by using prior information within a Bayesian framework. This research work discusses source reconstruction for EEG data using a Bayesian framework. In particular, MSP, LORETA and MNE are compared.
RESULTS: The results are compared in terms of variational free energy approximation to model evidence and in terms of variance accounted for in the sensor space. The results are taken for real time EEG data and synthetically generated EEG data at an SNR level of 10dB.
CONCLUSION: In brief, it was seen that MSP has the highest evidence and lowest localization error when compared to classical models. Furthermore, the plausibility and consistency of the source reconstruction speaks to the ability of MSP technique to localize active brain sources.
DISCUSSION: As surgery and radiotherapy alter the appearance of the breasts, distinguishing between recurrence and benign post-surgical changes can be challenging radiologically due to overlapping features. Despite this, differentiation between these two entities is usually possible by recognizing characteristic features of post-treatment sequelae and the evolution of the appearance of the conservatively treated breast by comparing interval findings on serial studies.
CONCLUSION: This pictorial review aims to describe the typical and unusual features of post-treated breasts in the multimodality imaging workup of an established breast care centre in a teaching hospital in Malaysia.
METHODS: In this study, we proposed an image feature extraction technique based on image segmentation with the fully convolutional neural network with eight stride pixel (FCN-8). A total of 290 radiographic images including both female and the male subject of age ranging from 0 to 18 were manually segmented and trained using FCN-8.
RESULTS AND CONCLUSION: The results exhibit a high training accuracy value of 99.68% and a loss rate of 0.008619 for 50 epochs of training. The experiments compared 58 images against the gold standard ground truth images. The accuracy of our fully automated segmentation technique is 0.78 ± 0.06, 1.56 ±0.30 mm and 98.02% in terms of Dice Coefficient, Hausdorff Distance, and overall qualitative carpal recognition accuracy, respectively.
METHODS: Six hemi-mandible samples were scanned using the i-CAT CBCT system. The scanned data was transferred to the OsiriX software for measurement protocol and subsequently into Mimics software to fabricate customized cutting jigs and 3D biomodels based on rapid prototyping technology. The hemi-mandibles were segmented into 5 dentoalveolar blocks using the customized jigs. Digital calliper was used to measure six distances surrounding the mandibular canal on each section. The same distances were measured on the corresponding cross-sectional OsiriX images and the 3D biomodels of each dentoalveolar block.
RESULTS: Statistically no significant difference was found when measurements from OsiriX images and 3D biomodels were compared to the "gold standard" -direct digital calliper measurement of the cadaveric dentoalveolar blocks. Moreover, the mean value difference of the various measurements between the different study components was also minimal.
CONCLUSION: Various distances surrounding the mandibular canal from 3D biomodels produced from the CBCT scanned data was similar to that of direct digital calliper measurements of the cadaveric specimens.
AIM: The purpose of this study is to perform a systematic review of the efficacy of Post-Mortem Computed Tomography (PMCT) scan compared with conventional autopsies gleaned from literature published in English between the year 2009 and 2016.
METHODOLOGY: A literature search was conducted in three databases, namely PubMed, MEDLINE, and Scopus. A total of 387 articles were retrieved, but only 21 studies were accepted after meeting the review criteria. Data, such as the number of victims, the number of radiologists and forensic pathologists involved, causes of death, and additional and missed diagnoses in PMCT scans were tabulated and analysed by two independent reviewers.
RESULTS: Compared with the conventional autopsy, the accuracy of PMCT scans in detecting injuries and causes of death was observed to range between 20% and 80%. The analysis also showed that PMCT had more advantages in detecting fractures, fluid in airways, gas in internal organs, major hemorrhages, fatty liver, stones, and bullet fragments. Despite its benefits, PMCT also could miss certain important lesion in a certain region such as cardiovascular injuries and minor vascular injuries.
CONCLUSIONS: This systematic review suggests that PMCT can replace most of the conventional autopsy in specific cases and is also a good complementary tool in most cases.