Muhammad Mobeen Movania
Other affiliations: DHA Suffa University
Bio: Muhammad Mobeen Movania is an academic researcher from Nanyang Technological University. The author has contributed to research in topics: Rendering (computer graphics) & Volume rendering. The author has an hindex of 7, co-authored 12 publications receiving 149 citations. Previous affiliations of Muhammad Mobeen Movania include DHA Suffa University.
TL;DR: Quality assessment using both quantitative evaluations and user studies suggests that the presented algorithm produces tone-mapped images that are visually pleasant and preserve details of the original image better than the existing methods.
Abstract: High-dynamic-range (HDR) images require tone mapping to be displayed properly on lower dynamic range devices. In this paper, a tone-mapping algorithm that uses histogram of luminance to construct a lookup table (LUT) for tone mapping is presented. Characteristics of the human visual system (HVS) are used to give more importance to visually distinguishable intensities while constructing the histogram bins. The method begins with constructing a histogram of the luminance channel, using bins that are perceived to be uniformly spaced by the HVS. Next, a refinement step is used, which removes the pixels from the bins that are indistinguishable by the HVS. Finally, the available display levels are distributed among the bins proportionate to the pixels counts thus giving due consideration to the visual contribution of each bin in the image. Quality assessment using both quantitative evaluations and user studies suggests that the presented algorithm produces tone-mapped images that are visually pleasant and preserve details of the original image better than the existing methods. Finally, implementation details of the algorithm on GPU for parallel processing are presented, which could achieve a significant gain in speed over CPU-based implementation.
TL;DR: A real-time virtual biopsy technique that can complement current diagnostic techniques and aid in targeted biopsy for better clinical outcomes is aim toward.
Abstract: Oral lesions are conventionally diagnosed using white light endoscopy and histopathology. This can pose a challenge because the lesions may be difficult to visualise under white light illumination. Confocal laser endomicroscopy can be used for confocal fluorescence imaging of surface and subsurface cellular and tissue structures. To move toward real-time "virtual" biopsy of oral lesions, we interfaced an embedded computing system to a confocal laser endomicroscope to achieve a prototype three-dimensional (3-D) fluorescence imaging system. A field-programmable gated array computing platform was programmed to enable synchronization of cross-sectional image grabbing and Z-depth scanning, automate the acquisition of confocal image stacks and perform volume rendering. Fluorescence imaging of the human and murine oral cavities was carried out using the fluorescent dyes fluorescein sodium and hypericin. Volume rendering of cellular and tissue structures from the oral cavity demonstrate the potential of the system for 3-D fluorescence visualization of the oral cavity in real-time. We aim toward achieving a real-time virtual biopsy technique that can complement current diagnostic techniques and aid in targeted biopsy for better clinical outcomes.
TL;DR: The aim is to achieve a real-time 3-D fluorescence imaging system that can be used for diagnostic imaging and guided biopsy procedures of oral cavity lesions in a clinical setting.
Abstract: The cancer burden is increasing worldwide and there is a need to develop new technologies for cancer diagnosis. Confocal laser endomicroscopy (CLE) is a minimally invasive optical technique that enables in vivo confocal imaging of tissue structures. With the use of fluorescent dyes, the technique allows confocal fluorescence endomicroscopy of tissue from surface to subsurface layers. CLE has been applied to the surveillance and diagnosis of cancer in numerous clinical studies recently, and also holds potential for optical and guided biopsy procedures. The first part of this mini review is focused on the application of CLE for cancer detection and surveillance. The second part is focused on the application of CLE to imaging of the oral cavity. We have previously demonstrated the potential of CLE for diagnostic imaging of oral cavity lesions. To move toward real-time 3-D imaging, we interfaced an endomicroscope to an embedded computing system. The prototype system is capable of automated image acquisition and real-time volume rendering. Rendering results provide topographical and depth information. Our aim is to achieve a real-time 3-D fluorescence imaging system that can be used for diagnostic imaging and guided biopsy procedures of oral cavity lesions in a clinical setting.
TL;DR: Two high-performance volume renderers are invented, namely, single-pass GPU ray caster and fast 3D texture slicer, for both mobile and desktop platforms, which outperforms the existing approaches in the literature.
Abstract: Now that high-performance computing systems can rely more on a cloud based infrastructure, it becomes much more important to have ubiquitous data processing and visualization capability. This will allow data sharing among numerous clients using shared data repositories through a secure web server. Thanks to the wide availability of GPU support in today's mobile devices such as smart phones and tablets, as well as the recently published WebGL standard, pervasive computing for high-quality and real-time volume rendering may be realized on such high-performance platforms. We have invented two high-performance volume renderers, namely, single-pass GPU ray caster and fast 3D texture slicer, for both mobile and desktop platforms. Rigorous experiments and performance assessments reveal that the proposed mobile 3D image rendering system outperforms the existing approaches in the literature.
TL;DR: A new deformation pipeline that is independent of the integration solver used and allows fast rendering of deformable soft bodies on the GPU by exploiting the transform feedback mechanism of the modern GPU to bypass the CPU read-back.
Abstract: We present a new deformation pipeline that is independent of the integration solver used and allows fast rendering of deformable soft bodies on the GPU. The proposed method exploits the transform feedback mechanism of the modern GPU to bypass the CPU read-back, thus, reusing the modified positions and/or velocities of the deformable object in a single pass in real time. The whole process is being carried out on the GPU. Prior approaches have resorted to CPU read-back along with the GPGPU mechanism. In contrast, our approach does not require these steps thus saving the GPU bandwidth for other tasks. We describe our algorithm along with implementation details on the modern GPU and finally conclude with a look at the experimental results. We show how easy it is to integrate any existing integration solver into the proposed pipeline by implementing explicit Euler integration in the vertex shader on the GPU.
TL;DR: The main aim of this review is to summarize the benefits of photoactivated and non-activated hypericin, mainly in preclinical and clinical applications, and to uncover the “dark side” of this secondary metabolite, focusing on MDR mechanisms.
Abstract: Hypericin (4,5,7,4',5',7'-hexahydroxy-2,2'-dimethylnaphtodianthrone) is a naturally occurring chromophore found in some species of the genus Hypericum, especially Hypericum perforatum L. (St. John's wort), and in some basidiomycetes (Dermocybe spp.) or endophytic fungi (Thielavia subthermophila). In recent decades, hypericin has been intensively studied for its broad pharmacological spectrum. Among its antidepressant and light-dependent antiviral actions, hypericin is a powerful natural photosensitizer that is applicable in the photodynamic therapy (PDT) of various oncological diseases. As the accumulation of hypericin is significantly higher in neoplastic tissue than in normal tissue, it can be used in photodynamic diagnosis (PDD) as an effective fluorescence marker for tumor detection and visualization. In addition, light-activated hypericin acts as a strong pro-oxidant agent with antineoplastic and antiangiogenic properties, since it effectively induces the apoptosis, necrosis or autophagy of cancer cells. Moreover, a strong affinity of hypericin for necrotic tissue was discovered. Thus, hypericin and its radiolabeled derivatives have been recently investigated as potential biomarkers for the non-invasive targeting of tissue necrosis in numerous disorders, including solid tumors. On the other hand, several light-independent actions of hypericin have also been described, even though its effects in the dark have not been studied as intensively as those of photoactivated hypericin. Various experimental studies have revealed no cytotoxicity of hypericin in the dark; however, it can serve as a potential antimetastatic and antiangiogenic agent. On the contrary, hypericin can induce the expression of some ABC transporters, which are often associated with the multidrug resistance (MDR) of cancer cells. Moreover, the hypericin-mediated attenuation of the cytotoxicity of some chemotherapeutics was revealed. Therefore, hypericin might represent another St. John's wort metabolite that is potentially responsible for negative herb-drug interactions. The main aim of this review is to summarize the benefits of photoactivated and non-activated hypericin, mainly in preclinical and clinical applications, and to uncover the "dark side" of this secondary metabolite, focusing on MDR mechanisms.
TL;DR: This review paper provides the necessary background to understand how optical fibers function, to describe the various categories of available fibers, and to illustrate how specific fibers are used for selected biomedical photonics applications.
Abstract: Optical fiber technology has significantly bolstered the growth of photonics applications in basic life sciences research and in biomedical diagnosis, therapy, monitoring, and surgery. The unique operational characteristics of diverse fibers have been exploited to realize advanced biomedical functions in areas such as illumination, imaging, minimally invasive surgery, tissue ablation, biological sensing, and tissue diagnosis. This review paper provides the necessary background to understand how optical fibers function, to describe the various categories of available fibers, and to illustrate how specific fibers are used for selected biomedical photonics applications. Research articles and vendor data sheets were consulted to describe the operational characteristics of conventional and specialty multimode and single-mode solid-core fibers, double-clad fibers, hard-clad silica fibers, conventional hollow-core fibers, photonic crystal fibers, polymer optical fibers, side-emitting and side-firing fibers, middle-infrared fibers, and optical fiber bundles. Representative applications from the recent literature illustrate how various fibers can be utilized in a wide range of biomedical disciplines. In addition to helping researchers refine current experimental setups, the material in this review paper will help conceptualize and develop emerging optical fiber-based diagnostic and analysis tools.
TL;DR: An effective blind quality assessment approach for TM images is proposed through a comprehensive consideration of their characteristics, which proves that the proposed approach is superior to the state-of-the-art no-reference IQA approaches.
Abstract: Nowadays, high-dynamic-range (HDR) imaging represents a prevailing trend and attracts much attention from both academic and industrial scholars. Since HDR images cannot be properly produced on the mainstream low-dynamic-range (LDR) displays, various tone-mapping operators or postprocessing technologies have been designed to transform HDR images into LDR images for visualization on LDR displays. However, it inevitably induces artifacts and distortions due to dynamic range compression. Besides, existing tone-mapped (TM) technologies cannot effectively handle all kinds of images with diverse contents and structures, leaving to a very challenging and urgent image quality assessment (IQA) problem. To cope with this challenge, in this paper, an effective blind quality assessment approach for TM images is proposed through a comprehensive consideration of their characteristics. More specifically, to dig out sufficient information from TM images, multiple quality-sensitive features are captured to fully represent different attributes, including colorfulness, naturalness, and structure. The connection between feature space and associated subjective ratings is established via a regression model. Extensive experiments on a recently released TM image database prove that the proposed approach is superior to the state-of-the-art no-reference IQA approaches.
TL;DR: CLE is a suitable and valid method for experts to diagnose oral cancer using the DOC-Score system and an accurate chair-side diagnosis of oral cancer is feasible with comparable results to the gold standard of histopathology—even in daily clinical practice for non-experienced raters.
Abstract: Confocal laser endomicroscopy (CLE) is an optical biopsy method allowing in vivo microscopic imaging at 1000-fold magnification. It was the aim to evaluate CLE in the human oral cavity for the differentiation of physiological/carcinomatous mucosa and to establish and validate, for the first time, a scoring system to facilitate CLE assessment. The study consisted of 4 phases: (1) CLE-imaging (in vivo) was performed after the intravenous injection of fluorescein in patients with histologically confirmed carcinomatous oral mucosa; (2) CLE-experts (n = 3) verified the applicability of CLE in the oral cavity for the differentiation between physiological and cancerous tissue compared to the gold standard of histopathological assessment; (3) based on specific patterns of tissue changes, CLE-experts (n = 3) developed a classification and scoring system (DOC-Score) to simplify the diagnosis of oral squamous cell carcinomas; (4) validation of the newly developed DOC-Score by non-CLE-experts (n = 3); final statistical evaluation of their classification performance (comparison to the results of CLE-experts and the histopathological analyses). Experts acquired and edited 45 sequences (260 s) of physiological and 50 sequences (518 s) of carcinomatous mucosa (total: 95 sequences/778 s). All sequences were evaluated independently by experts and non-experts (based on the newly proposed classification system). Sensitivity (0.953) and specificity (0.889) of the diagnoses by experts as well as sensitivity (0.973) and specificity (0.881) of the non-expert ratings correlated well with the results of the present gold standard of tissue histopathology. Experts had a positive predictive value (PPV) of 0.905 and a negative predictive value (NPV) of 0.945. Non-experts reached a PPV of 0.901 and a NPV of 0.967 with the help of the DOC-Score. Inter-rater reliability (Fleiss` kappa) was 0.73 for experts and 0.814 for non-experts. The intra-rater reliability (Cronbach’s alpha) of the experts was 0.989 and 0.884 for non-experts. CLE is a suitable and valid method for experts to diagnose oral cancer. Using the DOC-Score system, an accurate chair-side diagnosis of oral cancer is feasible with comparable results to the gold standard of histopathology—even in daily clinical practice for non-experienced raters.
TL;DR: This survey presents the past and present work on mobile volume rendering, and proposes a classification of the current efforts and covers aspects such as advantages and issues of the mobile platforms, rendering strategies, performance and user interfaces.
Abstract: Volume rendering has been a relevant topic in scientific visualization for the last decades. However, the exploration of reasonably big volume datasets requires considerable computing power, which has limited this field to the desktop scenario. But the recent advances in mobile graphics hardware have motivated the research community to overcome these restrictions and to bring volume graphics to these ubiquitous handheld platforms. This survey presents the past and present work on mobile volume rendering, and is meant to serve as an overview and introduction to the field. It proposes a classification of the current efforts and covers aspects such as advantages and issues of the mobile platforms, rendering strategies, performance and user interfaces. The paper ends by highlighting promising research directions to motivate the development of new and interesting mobile volume solutions.