Current Medical Imaging - Volume 14, Issue 6, 2018

Background: The area of image processing extends from basic image compression model to high end applications such as astronomical data processing and medical image processing. Images have vast features and coding them into lower bit rates results in the loss of information. Methods: This study proposes a novel hybrid approach to compress the image no loss of information and to maintain reduced processing overhead. Discussion: To validate the proposed approach, the suggested method is tested on different medical samples and the obtained results are compared with results retrived through the conventional JPEG based coding approach. Conclusion: The experimental results show that the proposed approach performs efficiently and can be implemented in realworld applications.

Background: Robust and accurate segmentation of the spine subdivided into individual vertebrae is necessary for subsequent diagnosis of illnesses related to the spine, particularly those requiring detection and classification of bone lesions. Based on correct vertebra segmentation, the current status of a disease under treatment - as well as its progress - can be determined and followed. Discussion: The problem is complicated by frequent heavy deformations of both the spine axis and individual vertebrae due to illness, so that some vertebrae may differ substantially from expected shapes or even be missing. This overview summarises and discusses so far published methods for spine and vertebrae segmentation in 3D CT thoracic data. Conclusion: It suggests a classification of these algorithms based on the used approaches, complexity of algorithms, as well as on achieved efficiencies.

Background: Medical Resonance Imaging (MRI) images degradation is still a challenging task. The noise is a compulsory destructive factor that gets added in MRI images due to several environmental and mechanical reasons. In this paper, an effort is made and a Genetic Programming (GP) based hybrid noise removal approach is proposed which reduces the effect of Rician noise of MRI images. Methods: The proposed approach preserves the structural and edges details of the regions of the images. The proposed GP approach uses Feature Extraction phase, GP based Optimal Expression module and Optimal Extraction based Estimation module to remove Rician noise. To validate the proposed approach, the proposed method is tested on different medical samples and the obtained results are compared with results retrieved through the existing comparative approaches. Conclusion: The experimental results show that the proposed approach performs efficiently and can be implemented in real world applications.

Background: Prostate cancer is the second most prevailing cancer among men worldwide. In the most cases, prostate cancer is slowly progressing, whereas, in some cases, it is a rapidly progressing disease leading to the significantly high mortality rate. Thus, there is still demand for prostate-specific imaging in order to provide image-guided early diagnosis and for the provision of patient-specific therapy. Discussion: Besides discussing traditional diagnostic approaches, this review illustrates a perspective on prostate cancer imaging summarizing current imaging approaches with a special focus on Prostate Specific Membrane Antigen (PSMA), Bombesin (BN) and Androgen Receptor (AR) targeted imaging using Positron Emission Tomography (PET) and Single Positron Emission Computed Tomography (SPECT) based on 99mTc and other radiotracers. Here, the prostate biology is reconsidered for nuclear imaging as future modality for early, rapid and efficient diagnosis of prostate cancer. Conclusion: Future direction in prostate cancer imaging involves the development of androgen receptor based imaging using nonsteroidal antiandrogen agent for early diagnosis of prostate cancer.

Introduction: Metabolome reflects the sum of all life processes in the cell-tissue-organ, belonging to all the systems that constitute the individual and it refers to metabolites included in a cell, tissue or organism. Since metabolites are various, in terms of chemical species and concentrations, it is necessary to conduct metabolite analysis with a variety of different analytical techniques. Imaging is the main part of these modern diagnosis pathways. Discussion: A narrative review of all the relevant papers known to the authors was conducted, researching the Pubmed database. Considering this last definition of the multimodal in vivo - in vitro approach, an essential and versatile diagnostic technique can be regarded as the most recent and crucial innovation in modern diagnostics: Nuclear Magnetic Resonance (NMR). For the in vitro application, NMR has become an important tool for metabolomics. Metabolomics is defined as the quantitative and qualitative analysis of a large number of metabolites that are intermediate or final products of all the metabolic pathways in a biological system. Metabolomics aims to obtain a global understanding of living organisms to a deeper level than has so far been achieved through genomics and proteomics. This property is of great clinical importance in light of recent definitions of health and disease. Conclusion: This review highlights the workflow of a typical metabolomics study and summarises the most up-to-date results obtained from the latest in vivo imaging techniques and their technologies, focussing on the future perspective of in vivo MRS metabolomics.

Objective: To evaluate the correlation between smoking and types of coronary atherosclerotic plaques using Double-Source Computed Tomography (DSCT) angiography. Methods: Patients who underwent DSCT Coronary Angiography (DSCTCA) at our hospital between April 2012 and April 2013 were enrolled and divided into a smoking group and a nonsmoking group according to their response to a questionnaire of smoking. Patients with a familial genetic history of coronary or concomitant diabetes mellitus, hypertension, or hyperlipidemia were considered and divided into two groups according to their smoking history, as 200 smokers and 200 non-smokers were selected for the study. The incidence rates, distribution characteristics, and types of plaque were identified and compared between the two groups. Results: The incidences of mixed plaques (44.7% vs. 21.9%) and non-calcified plaques (38.7% vs. 67.9%) were significantly different between the smoking group and the non-smoking group (both P <0.05). When the data were adjusted for age, sex, and weight index, smoking was an independent risk factor for formation of mixed plaques. The smoking group was subdivided according to the Smoking Index (SI) and a comparison showed that the incidence of mixed plaques increased with increasing SI. Conclusion: DSCTCA can accurately evaluate differences in coronary atherosclerotic plaques between smokers and non-smokers. Smokers are more likely to develop mixed plaques and are at higher risk of cardiovascular events, and the plaques are distributed more widely.

Background: As world population gets older, more cases of collapse fracture, disc herniation, vertebral osteomyelitis and chord compression and surgeries on spine are noted. One of the complications is pain and in differential diagnosis are infectious and non-infectious processes. The method of choice for the diagnosis of infection in spinal column is MRI, however it is inapplicable in many cases. In addition, other imaging modalities like CT scan, PET or bone scintigraphy have their own limitations. UBI is a polypeptide which is taken by bacteria in the cell wall and therefore Tc99m-UBI has been used to detect infectious processes with promising results. Objective: The aim of this study was to use Tc 99m-UBI to differentiate infectious process from other etiologies in patients with pain in spinal column in which other diagnostic methods were not conclusive. Methods: We investigated 30 patients (20 females and 10 males) with back-pain. 11 had a history of surgical manipulation on spine. All patients first were scanned and then were treated and followed by a neurosurgeon and an infectious disease specialist. Both treating physicians were blind to the result of the scan and final data (after 2 years follow up) were analyzed by a third physician. Results: The result showed qualitative assessment and quantitative interpretation of UBI scan (using target to background threshold of 1.29) have 33% sensitivity and 95% specificity and 33% and 80% specificity respectively in the diagnosis of osteomyelitis of spinal column. Conclusion: These results suggest that UBI scan is not recommended in initial assessment but may be helpful for the diagnosis of patient with non-infectious processes; however more studies are needed for precise conclusion.

Background: MRI which stands for Magnetic Resonance Imaging is commonly used to capture images of internal body organs, functionality and structure. Manual analysis is usually performed by Radiologists on a large set of MR images in order to detect brain tumor. Aims: This research aims to improve automated brain MR image classification and tumor segmentation using phase congruency. Methods: The skull part is removed from brain MR image by applying converging square algorithm and phase congruency based edge detection method. Features are then extracted from the segmented brain portion using discrete wavelet transforms. In order to minimize the extracted feature set, we applied the principal Component Analysis algorithm. The MR images are classified into tumorous and non-tumorous using Multilayer perceptron and compared with other classifiers such as K-Nearest Neighbor, Naïve Bayes, and Support Vector Machines (SVM) along with discrete cosine and discrete cosine transform features. The tumor is segmented using Fuzzy C-mean and reconstructed tumor 3D model to measure the volume, location and shape accurately. Results & Conclusion: Experimental results are obtained by testing the proposed method on a dataset of 19 patients with a total number of 2920 brain MR images. The proposed method achieved an accuracy of 99.43% for classification which is higher as compared to other current studies.

Background: These days, many attempts have been done to specify the size and location of aneurysms, leading to more successful surgical operation and less bleeding risk. In this paper, a novel method is proposed to extract brain aneurysms from two dimensional x-ray angiography videos, automatically. Methods: The most acute challenges in detecting brain aneurysm are the complexity of vessel structures and shape similarity between the aneurysm and vessel overlaps and vessel cross sections. Therefore, researchers regarded removing vessel structures as an initial and crucial step to detect aneurysm. Since the circularity feature is the most distinctive criteria for physicians to detect aneurysm, firstly, we proposed a robust method based on Fast Circlet Transform (FCT) to localize the aneurysm without needing to remove vessel structures. Then, to segment the detected aneurysm more accurately, a modified Level Set algorithm is proposed. Finally, our proposed method is quantitatively evaluated on two different datasets with different views, shapes, sizes, locations and contrast. Results & Conclusion: Experimental results show that the proposed system is reliable without dealing with vessel structure removal challenges, reluctant false positive candidates, hard parameter tuning and poor edge gradient.

Objective: The aim of this study is to examine the diffusional changes in the vitreous humor in multiple sclerosis and Beh's disease. Materials and Methods: Apparent diffusion coefficient values were investigated in diffusion magnetic resonance imaging scans of a total 111 vitreous, 31 of which were Beh's disease patients, 40 had multiple sclerosis and 40 were healthy volunteers. Then, multiple sclerosis and Beh's disease group were statistically compared with healthy volunteers and their apparent diffusion coefficient values amongst themselves. Results: There was no significant difference in terms of age and sex distribution among the three study groups (p>0.05). While there was no significant difference between multiple sclerosis and control groups (p>0.05), apparent diffusion coefficient values of Beh's patients were significantly lower than multiple sclerosis and control groups (p<0.001). There was no significant difference between the patients with uveitis and those without uveitis in Beh's disease. The apparent diffusion coefficient value of 2934,3(x10-6 mm2/s) had a very high sensitivity and specificity (72.42-92.5%) for the Behçet's group, and by the use of ROC curve analysis, the detected cut off value for Behçet's disease was ≤2934,3(x10-6 mm2/s). Conclusion: Our study showed that diffusion values in the vitreous humor were found to be decreased in patients with Beh's disease, in comparison with the multiple sclerosis and the control groups. To the best of our knowledge, this has not been reported before.

Purpose: The aim of this study was to investigate the changes of CD3 and CD20 in the microenvironment of rabbit peripheral lung cancer before and after microwave ablation (MA). Methods: Twenty-four rabbits with lung VX2 tumor were randomly divided into four groups (n = 6 in each group). Ultrasound-guided MA was gone using 40 W powers as the treatment mode for about 60s. The animals were sacrificed by injecting anesthetic into the ear vein before and after MA. The thoracic ribs were cut off and the lung lobes were removed completely with tumor and then washed with saline. Part of the organization placed into 4% formaldehyde for pathological examination; part placed into 2.5% glutaraldehyde for the electron microscopy. Result: The histological features of ablation lesions showed as morphological abnormalities of tumor cells, cell and nuclear elongated by heat; the cells of alveolar wall degeneration and necrosis. The alveolar wall ruptured and alveolar structure disappeared. Blood cells and inflammatory cells appeared in the alveolar interstitial and a large number of serous exudated. The positive cell numbers of CD3 and CD20 cells at 2 weeks after MA were significantly different from those before MA and at 3 days and 1 week after MA (P< 0.01). There was no significant difference in the positive cells of CD3 and CD20 before and 3 days and 1 week after MA. Conclusion: The number of immune cells in tumor adjacent tissue increased significantly after MA and the level of local anti-tumor immune cells was also increased.

Background: Cancer that develops in any of the parts of the breast is known as breast cancer. To reduce the breast cancer fatality, Computer Aided Diagnosis can assist physicians for accurate diagnosis. Objective: To improve the performance of breast cancer diagnosis using fusion of local binary and ternary patterns from ultrasound B mode and elastography images. Methods: In this work, the fusion of texture features of more sensitive B mode and more specific elastography images is suggested for breast cancer diagnosis. Both the images are speckle removed and segmented for detecting the tumorous region. Local Binary Pattern (LBP) and Local Ternary Pattern (LTP) features are extracted from both images and reduced by Principal Component Analysis or Canonical Correlation Analysis (CCA). Serial or parallel fusion is applied on the reduced features followed by Support Vector Machine classifier. Results: Use of LTP provides better accuracy (94.7% for B mode and 93.8% for Elastography) than existing systems. The accuracy is further increased to 96.5% for LBP and 98.2% for LTP with serial fusion using CCA. This shows an improvement of 1.9% and 3.7% with respect to the B mode system with LTP. As specificity reaches 100%, no false positives have been detected. Conclusion: LTP is more immune to noise and CCA transforms the LTPs of the two images so that the transformations have maximum cross correlation and minimum auto correlation. This provides more relevant features and improves the performance. Hence, the proposed system could assist doctors in diagnosing the breast tumors in better way.

Background: Computer Aided Diagnosis (CADx) with screening mammography could help radiologists and doctors in reliable and accurate identification of breast cancer at the preliminary stage. Objective: To propose an early diagnosis technique using fusion of texture features extracted from both Medio Lateral Oblique (MLO) and Cranio Caudal (CC) view mammograms. Methods: The proposed two-view CADx system segments the tumour region by fuzzy c-means clustering. The texture features extracted from MLO and CC view are reduced by Principal Component Analysis (PCA) or Canonical Correlation Analysis (CCA) and fused serially or parallelly followed by support vector machine classifier (SVM). Results: An improvement in accuracy of 4.4% and 7.05% was achieved with serial fusion using CCA for DDSM and INbreast datasets respectively. It is also observed that there is a significant improvement in specificity, F1 measure, kappa coefficient and Balanced Classification Rate (BCR) with serial fusion using CCA for all four texture features irrespective of the datasets. A significant improvement in BCR of 3.26% and 7.52% was achieved with LAWs feature for DDSM and INbreast respectively. Conclusion: LAWs provide almost all types of texture variations such as edges, ripples and spots. CCA transforms the feature vectors in such a way that the transformed features have maximum cross correlation and minimum auto correlation. Hence, it provides more relevant features and consequently improves the performance. Thus, our method could be used to assist doctors in enhancing the effectiveness of breast cancer diagnosis and start the treatment in earlier stage of the disease.

Background: Image compression is an area of research that has many applications spanning different technological fields; among the most important of these fields is that of mammography images compression. With whole mammography images becoming increasingly practical and cost-effective, the need for a superior space-saving algorithm is obvious. Also, it becomes important that reconstructed image achieves high compression rates without any alterations from its original form in order to maintain the image quality which has an influence on the accuracy of radiologist diagnosis. Methods: This paper presents a lossless compression algorithm that is based on image enhancement, Haar wavelet transform and differential Pulse Code Modulation (DPCM) to optimize the compression of 50 mammography images. Image enchantment is implemented by two techniques; Histogram Equalization (HE) and top-hat filtering. The performance of compressed images is measured by Compression Ratio (CR), Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and time consumption. Results: This proposed algorithm is compared to existing ones and the results show that the compression ratio has increased from 6.44 to 26.841.

Purpose: The purpose of this study was to compare the value of 99mTc-octreotide scintigraphy and planar X-ray mammography in the diagnosis of breast cancer. Methods: A total of 65 patients with suspected breast cancer were enrolled. All patients underwent 99mTc-octreotide scintigraphy and planar X-ray mammography. The diagnostic efficiencies of 99mTc-octreotide scintigraphy and planar X-ray mammography were compared based on postsurgery pathology. Results: The sensitivities of 99mTc-octreotide scintigraphy and planar X-ray mammography in the diagnosis of breast cancer were 90.6% and 66.0%, respectively. The specificities were 00% and 41.7%, while the accuracies were 91.4% and 66.7%, respectively. When 99mTc-octreotide scintigraphy was combined with planar X-ray mammography, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value for breast cancer were 96.2%, 100%, 94.1%, 87.9%, and 36.4%, respectively. Conclusion: The diagnostic efficiency of 99mTc-octreotide scintigraphy for breast cancer is superior to that of planar X-ray mammography. When combined with planar X-ray mammography, the diagnostic efficiency of 99mTc-octreotide scintigraphy for breast cancer is further increased.

Background: The male-based infertility test known as a spermiogram involves a manual count using a Makler counting chamber. There is a need to develop an automated sperm-counting system to provide more precise diagnoses. To that end, the automatic detection of Regions of Interest (ROI) in Makler images constitutes the first phase to using the advantages of the Makler chamber in a computerized counting system. Methods: ROI are defined between grids, hence, another challenging issue, that of exact grid detection, is examined. In this study, initially we reviewed several line detection algorithms with their applications and possible usage on the grid-detection problem of Makler images. Next, a combinational grid-detection technique, particularly for Makler images, was improved upon. Results: In summary, the Hough transform method has been enhanced by a combined approach of using Line Segment Detector, the clustering of slope angles, and post processing. The K-means method is deployed to refine the grids and to find the direction of grid lines to use in Hough transform. In the grid-detection step, the presented technique is evaluated with a template-matching technique following the Sørensen-Dice index. It gives 95.3% accuracy and 88.5% F-measure scores. Discussion: ROI extraction is performed based on grid detection output by multiple logical queries. Each extracted region, clarified from the grid lines, was identically examined for sperm count. Fuzzy c-means clustering was first performed to segment the objects in ROI, then blob analysis was utilized to eliminate non-sperm objects. Coclusion: The proposed sperm analysis approach was then compared to the visual assessment technique. Results indicate that the proposed system might be useful in laboratories, but still needs to be improved in the feature extraction process.

Background: In Magnetic Resonance (MR) image reconstruction, Higher Degree Total Variation (HDTV) using high-order directional derivatives outperforms total variation-based method in preserving edge information and suppressing unfavourable staircase artifacts. Traditional HDTV regularization, however, takes the form of L1-based, which is not the most straightforward way to maximize sparsity prior. Previous work has shown that nonconvex Lp-norm is potentially more effective than L1-norm in promoting sparsity. Methods: This work develops a Higher Degree Total p-variation (HDTpV) regularization model to enhance the sparsity utilization of HDTV and offers more accurate solutions for MR image reconstruction issues. To resolve the nonconvex optimization issue of the HDTpV minimization model, Split Bregman (SB) method was adopted to translate the original constrained problem into a succession of unconstrained subproblems, which can be solved by fast Fourier transform and generalized pshrinkage mapping. The qualitative and quantitative simulation experiments are conducted to demonstrate the accuracy and efficiency of the proposed method. Results & Conclusion: On the whole, improved performance is exhibited by the proposed method over the original HDTV-based method while applied to compressed MR image reconstruction.

Objective: To evaluate the clinical significance of percutaneous puncture biopsy guided by fused and 3D-reconstructed Positron-Emission Tomography (PET)/Computed Tomography (CT) images in diagnosing deep lesions. Methods: According to the CT morphological information obtained from 47 patients who need to undertake percutaneous needle biopsy after PET/CT examination, two associate chief physicians selected the lesion with SUVmax >2.5 as the target spot of the surgery. The two operators performed a first CT scan of the lesion to define an optimal puncture path. After CT scan, images with a thickness of 1.5 mm were transmitted to the processing center, then fused and 3D-reconstructed with PET images. When the target lesion area was clearly identified and selected, an 18G biopsy needle was threaded through the trocar to incise the tissues inside the lesion. Pathological examination of the target lesion tissue was accomplished. Results: Using images obtained from the same instrument, location, shape and 2-[18F]-fluoro-2- deoxy-D-glucose (FDG) uptake of deep lesions were clearly and dimensionally displayed, thus the biopsy needle was precisely guided through its pathway to the hypermetabolic lesion. All percutaneous puncture biopsies were successfully accomplished (100%), with an accuracy of 97.9% (46/47) and an average surgical duration of 17.3±9.5 min. All post-operative pathological examinations achieved a precise diagnosis. Conclusions: With the guidance of fused and 3D-reconstructed PET/CT images, the lesion could be precisely identified. Hence, percutaneous needle biopsy obtained from morphology-guided to metabolism-guided techniques has a clear significance in clinical practice.

Background: Nasopharyngeal adenoid hypertrophy (NAH) is a frequent incidental finding on head and neck imaging in children. Objective: The study aimed to investigate magnetic resonance imaging (MRI) findings and prevalence of NAH after Bone Marrow Transplantation (BMT) in children with hemato-oncological diseases. Methods: Between February 2013 and January 2018, BMT was performed in 202 pediatric patients. Forty-three patients (20 girl, 23 boy; age range, 1-19 years; mean age 9.4 years) who underwent at least two head and neck MRI before and after BMT were included in the study. Posttransplantation NAH (PTNAH) was considered when anterior-posterior (A-P) diameter of adenoid increased on post-BMT MRI relative to the previous MRI performed before BMT. Adenoid was evaluated for symmetry, cystic and septal content, signal intensity and contrast enhancement. Results: Fourteen (32.5%) of 43 patients demonstrated PTNAH (7 boy, 7 girl; age range, 1-19 years; mean age, 10.5 years). Six (43%) of 14 patients were diagnosed with thalassemia. Six (50%) of 12 patients with thalassemia revealed PTNAH. The mean time intervals were 116 days and 213 days, respectively. The mean A-P diameter of adenoid was 5.2 mm before BMT which was 7.8 mm after BMT. All lesions were symmetric, isointense on T1-weighted (W), mild hyperintense on T2W and marked hyperintense on T2W TIRM images with slight contrast enhancement. Most of the lesions showed diffusion restriction and multiple longitudinal septa. Only one lesion revealed retention cysts. Conclusion: NAH is a common finding after BMT in children. Awareness of imaging characteristics is important to prevent invasive procedures like biopsy and surgery.

Introduction: In this report, we present a case of an 11-year-old female that was diagnosed with acute abdomen secondary to E. vermicularis infestation in appendix vermiformis. Preoperative ultrasonography demonstrated parasitic blockage of the appendix without signs of appendicitis. Although pyrantel pamoate was given, acute abdominal signs did not disappear and the patient subsequently underwent surgery. Discussion: This case report documents clear ultrasound images of pinworm infestation of the appendix that has not previously been documented in the literature. Conclusion: We feel consider that preoperative diagnosis of Enterobius Vermicularis is possible with the use of ultrasonography, and provides us to and is helpful for the use of anti-helminthic therapy before operation that ensures a safer intervention.