Histogram Equalization for Improving Quality of Low-resolution Ultrasonography Images

The current development of digital image processing techniques have been very rapid. Application of digital image processing both hardware and software are available with a variety of features as a form of superiority. Medical ultrasonography is one of the results of digital image processing technology. It is a kind of diagnostic imaging technique with ultrasonic that is used to produce images of internal organs and muscles, size, structure, and wound pathology, which makes this technique is useful for checking organ. However the images produced by low resolution ultrasonography device is not fully produce clear information. In this research we use histogram equalization to improve image quality. In this paper we emphasize on the comparison of the two methods in the histogram equalization, namely Enhance Contrast Using Histogram Equalization (ECHE) and Contrast-Limited Adaptive Histogram Equalization (CLAHE). The results showed that CLAHE give the best results, with the parameter value Nbins 256 and Distribution Rayleigh with MSE value 9744.80 and PSNR value 8.284150

A versatile imaging system for in vivo small animal research

In vivo small animal imaging has become an essential technique for molecular biology studies. However, requirements of spatial resolution, sensitivity and image quality are quite challenging for the development of small-animal imaging systems. The capabilities of the system are also significant for carrying out small animal imaging in a wide range of biological studies. The goal of this dissertation is to develop a high-performance imaging system that can readily meet a wide range of requirements for a variety of small animal imaging applications. Several achievements have been made in order to fulfill this goal.;To supplement our system for parallel-hole single photon emission computed tomography (SPECT) based upon a 110 mm diameter circular detector, we have developed novel compact gamma cameras suitable for imaging an entire mouse. These gamma cameras facilitate multi-head (\u3e2) parallel-hole SPECT with the mouse in close proximity to the detector face in order to preserve spatial resolution. Each compact gamma cameras incorporates pixellated Nal(Tl) scintillators and a pair of Hamamatsu H8500 position sensitive photomultiplier tubes (PSPMTs). Two types of copper-beryllium parallel-hole collimators have been designed. These provide high-sensitivity imaging of I-125 or excellent spatial resolution over a range of object-detector distances. Both phantom and animal studies have demonstrated that these gamma cameras perform well for planar scintigraphy and parallel-hole SPECT of mice.;To further address the resolution limitations in parallel-hole SPECT and the sensitivity and limited field of view of single-pinhole SPECT, we have developed novel multipinhole helical SPECT based upon a 110 mm diameter circular detector equipped with a pixellated Nal(Tl) scintillator array. A brass collimator has been designed and produced containing five 1 mm diameter pinholes. Results obtained in SPECT studies of various phantoms show an enlarged field of view, very good resolution and improved sensitivity using this new imaging technique.;These studies in small-animal imaging have been applied to in vivo biological studies related to human health issues including studies of the thyroid and breast cancer. A re-evaluation study of potassium iodide blocking efficiency in radioiodine uptake in mice suggests that the FDA-recommended human dose of stable potassium iodide may not be sufficient to effectively protect the thyroid from radioiodine contamination. Another recent study has demonstrated that multipinhole helical SPECT can resolve the fine structure of the mouse thyroid using a relatively low dose (200 muCi). Another preclinical study has focused on breast tumor imaging using a compact gamma camera and an endogenous reporter gene. In that ongoing study, mammary tumors are imaged at different stages. Preliminary results indicate different functional patterns in the uptake of radiotracers and their potential relationship with other tumor parameters such as tumor size.;In summary, we have developed a versatile imaging system suitable for in vivo small animal research as evidenced by a variety of applications. The modular construction of this system will allow expansion and further development as new needs and new opportunities arise

Entwicklungen und Untersuchungen zur Bildgebung der Schilddrüse: 124Iod-PET/CT, 3D-Ultraschall und nuklearmedizinisch-sonographische Bildfusion

In der etablierten Schilddrüsenbildgebung existieren trotz des bereits hohen Standards begrenzende Faktoren. Methodische und technische Neuerungen erscheinen mithin sinnvoll und geboten. Die vorliegende Habilitationsschrift stellt die Entwicklung und Erprobung neuer Konzepte der Schilddrüsendiagnostik in drei Teilgebieten vor: *Durch die 124Iod-Niedrigaktivitäts-PET/Niedrigdosis-CT wird (i) die Ortsauflösung der herkömmlichen Szintigraphie übertroffen und die Detektierbarkeit kleinerer Strukturen sowie anatomischer Details verbessert. Durch den parallel akquirierten CT-Datensatz können (ii) zusätzliche Erkenntnisse zur Schilddrüse sowie deren Beziehung zu Nachbarorganen gewonnen werden. Darüber hinaus sind (iii) im Rahmen der Vorbereitung von Radiojodtherapien prätherapeutische Uptake-Messungen möglich. *Der 3D-US ermöglicht (i) den lückenlosen Scan der Schilddrüse und (ii) die vollständige digitale Archivierung des Untersuchungsvolumens im PACS. Dadurch ergeben sich auf Schnittbildworkstations die Vorteile (iii) des Second Readings, (iv) des Side-by-Side-Vergleichs mit vorangegangenen 3D-US-Studien und anderen Schnittbildverfahren. Darüber hinaus kann (v) eine nachträgliche Datenverarbeitung (Processing) erfolgen. *Die Einbeziehung des Ultraschalls in das Konzept der Fusions- bzw. Hybridbildgebung hat gezeigt, dass die räumliche Verknüpfung und bildliche Überlagerung der morphologisch-sonographischen Informationen mit den nuklearmedizinisch-funktionellen Bilddaten erfolgen kann. Aus dem klinischen Potential der Methoden einerseits, sowie den geschilderten Limitationen andererseits ergeben sich Implikationen für die Zukunft. Zunächst sind die apparativ-technische Weiterentwicklung der Verfahren sowie eine Optimierung der informationstechnischen Einbindung notwendig. Darüber hinaus muss eine Entwicklung hin zu einer zeitsparenden und einfachen Anwendbarkeit erfolgen, um einen rationellen klinischen Workflow zu ermöglichen und personelle Ressourcen zu schonen

Computational methods for the analysis of functional 4D-CT chest images.

Medical imaging is an important emerging technology that has been intensively used in the last few decades for disease diagnosis and monitoring as well as for the assessment of treatment effectiveness. Medical images provide a very large amount of valuable information that is too huge to be exploited by radiologists and physicians. Therefore, the design of computer-aided diagnostic (CAD) system, which can be used as an assistive tool for the medical community, is of a great importance. This dissertation deals with the development of a complete CAD system for lung cancer patients, which remains the leading cause of cancer-related death in the USA. In 2014, there were approximately 224,210 new cases of lung cancer and 159,260 related deaths. The process begins with the detection of lung cancer which is detected through the diagnosis of lung nodules (a manifestation of lung cancer). These nodules are approximately spherical regions of primarily high density tissue that are visible in computed tomography (CT) images of the lung. The treatment of these lung cancer nodules is complex, nearly 70% of lung cancer patients require radiation therapy as part of their treatment. Radiation-induced lung injury is a limiting toxicity that may decrease cure rates and increase morbidity and mortality treatment. By finding ways to accurately detect, at early stage, and hence prevent lung injury, it will have significant positive consequences for lung cancer patients. The ultimate goal of this dissertation is to develop a clinically usable CAD system that can improve the sensitivity and specificity of early detection of radiation-induced lung injury based on the hypotheses that radiated lung tissues may get affected and suffer decrease of their functionality as a side effect of radiation therapy treatment. These hypotheses have been validated by demonstrating that automatic segmentation of the lung regions and registration of consecutive respiratory phases to estimate their elasticity, ventilation, and texture features to provide discriminatory descriptors that can be used for early detection of radiation-induced lung injury. The proposed methodologies will lead to novel indexes for distinguishing normal/healthy and injured lung tissues in clinical decision-making. To achieve this goal, a CAD system for accurate detection of radiation-induced lung injury that requires three basic components has been developed. These components are the lung fields segmentation, lung registration, and features extraction and tissue classification. This dissertation starts with an exploration of the available medical imaging modalities to present the importance of medical imaging in today’s clinical applications. Secondly, the methodologies, challenges, and limitations of recent CAD systems for lung cancer detection are covered. This is followed by introducing an accurate segmentation methodology of the lung parenchyma with the focus of pathological lungs to extract the volume of interest (VOI) to be analyzed for potential existence of lung injuries stemmed from the radiation therapy. After the segmentation of the VOI, a lung registration framework is introduced to perform a crucial and important step that ensures the co-alignment of the intra-patient scans. This step eliminates the effects of orientation differences, motion, breathing, heart beats, and differences in scanning parameters to be able to accurately extract the functionality features for the lung fields. The developed registration framework also helps in the evaluation and gated control of the radiotherapy through the motion estimation analysis before and after the therapy dose. Finally, the radiation-induced lung injury is introduced, which combines the previous two medical image processing and analysis steps with the features estimation and classification step. This framework estimates and combines both texture and functional features. The texture features are modeled using the novel 7th-order Markov Gibbs random field (MGRF) model that has the ability to accurately models the texture of healthy and injured lung tissues through simultaneously accounting for both vertical and horizontal relative dependencies between voxel-wise signals. While the functionality features calculations are based on the calculated deformation fields, obtained from the 4D-CT lung registration, that maps lung voxels between successive CT scans in the respiratory cycle. These functionality features describe the ventilation, the air flow rate, of the lung tissues using the Jacobian of the deformation field and the tissues’ elasticity using the strain components calculated from the gradient of the deformation field. Finally, these features are combined in the classification model to detect the injured parts of the lung at an early stage and enables an earlier intervention

Enter the matrix:On how to improve thyroid nodule management using 3D ultrasound

Roughly two-thirds of the adult population has a thyroid nodule, of which 90% are benign. Of the adults that have a nodule, approximately 5% will experience symptoms that include a feeling of a marble stuck in the throat, difficulty swallowing and breathing, and cosmetic complaints. Thyroid nodule management primarily makes use of ultrasound as the imaging modality for diagnosis, image guidance during therapy (radiofrequency ablation i.e. RFA), and follow-up. Although ultrasound is relatively easy to apply, it is hard to standardize for repeated measurements and across various users. Further, RFA can benefit from 3D imaging information and a planning and navigation system to improve clinical outcome. These challenges may be overcome by using 3D ultrasound. In this thesis, two phantoms were created on which these methods can be developed. Further, it offers insight into the use of 2D and 3D ultrasound for thyroid nodule management.To assess the impact of changes to an intervention, a baseline was determined of the effectiveness of RFA in Dutch hospitalsUsing a simple phantom, we have shown that utilizing a volume-based measurement technique, that the matrix transducer offers, results in improved measurement accuracy. The more complex, anthropomorphic, phantom serves as a platform on which thermal treatments, such as RFA, can be improved. Using this phantom, we have shown that the impact of 2D and 3D ultrasound on RFA efficacy does not differ from one another; however, the matrix transducer might be more user-friendly for needle placement due to the dual-plane imaging. An additional use case for these phantoms is their capacity to compare dominant and non-dominant hand ablations, as well as serve as a training platform. Additional research is required that employs more operators to find stronger evidence supporting a difference between the ablating hands and the difference in effect of 2D and 3D ultrasound guidance.To make full use of 3D ultrasound, stitching algorithms should be integrated into the ultrasound systems to acquire larger volumes. These can then be processed by deep-learning algorithms for use in computer-aided diagnosis and intervention systems. To further improve the applicability of 3D ultrasound in the clinic, integrating analysis methods such as 3D elastography and 3D Doppler is suggested

Machine Learning/Deep Learning in Medical Image Processing

Many recent studies on medical image processing have involved the use of machine learning (ML) and deep learning (DL). This special issue, “Machine Learning/Deep Learning in Medical Image Processing”, has been launched to provide an opportunity for researchers in the area of medical image processing to highlight recent developments made in their fields with ML/DL. Seven excellent papers that cover a wide variety of medical/clinical aspects are selected in this special issue

[¹⁸F]fluorination of biorelevant arylboronic acid pinacol ester scaffolds synthesized by convergence techniques

Aim: The development of small molecules through convergent multicomponent reactions (MCR) has been boosted during the last decade due to the ability to synthesize, virtually without any side-products, numerous small drug-like molecules with several degrees of structural diversity.(1) The association of positron emission tomography (PET) labeling techniques in line with the “one-pot” development of biologically active compounds has the potential to become relevant not only for the evaluation and characterization of those MCR products through molecular imaging, but also to increase the library of radiotracers available. Therefore, since the [18F]fluorination of arylboronic acid pinacol ester derivatives tolerates electron-poor and electro-rich arenes and various functional groups,(2) the main goal of this research work was to achieve the 18F-radiolabeling of several different molecules synthesized through MCR. Materials and Methods: [18F]Fluorination of boronic acid pinacol esters was first extensively optimized using a benzaldehyde derivative in relation to the ideal amount of Cu(II) catalyst and precursor to be used, as well as the reaction solvent. Radiochemical conversion (RCC) yields were assessed by TLC-SG. The optimized radiolabeling conditions were subsequently applied to several structurally different MCR scaffolds comprising biologically relevant pharmacophores (e.g. β-lactam, morpholine, tetrazole, oxazole) that were synthesized to specifically contain a boronic acid pinacol ester group. Results: Radiolabeling with fluorine-18 was achieved with volumes (800 μl) and activities (≤ 2 GBq) compatible with most radiochemistry techniques and modules. In summary, an increase in the quantities of precursor or Cu(II) catalyst lead to higher conversion yields. An optimal amount of precursor (0.06 mmol) and Cu(OTf)2(py)4 (0.04 mmol) was defined for further reactions, with DMA being a preferential solvent over DMF. RCC yields from 15% to 76%, depending on the scaffold, were reproducibly achieved. Interestingly, it was noticed that the structure of the scaffolds, beyond the arylboronic acid, exerts some influence in the final RCC, with electron-withdrawing groups in the para position apparently enhancing the radiolabeling yield. Conclusion: The developed method with high RCC and reproducibility has the potential to be applied in line with MCR and also has a possibility to be incorporated in a later stage of this convergent “one-pot” synthesis strategy. Further studies are currently ongoing to apply this radiolabeling concept to fluorine-containing approved drugs whose boronic acid pinacol ester precursors can be synthesized through MCR (e.g. atorvastatin)