Visitsattapongse, Sarinporn
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Preferred name
Visitsattapongse, Sarinporn
Alternative Name
Visitsattapongse, S.
Main Affiliation
Email
sarinporn.vi@kmitl.ac.th
43 results
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Item type:Publication, Store-operated calcium entry facilitates LPS-induced superoxide anion-dependent macrophage extracellular traps(2025-07-09) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Analysis of Deep Learning-Based Phase Retrieval Algorithm Performance for Quantitative Phase Imaging Microscopy(2022-05-01); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Biosensors for Bacillus sphaericus detection to diagnostic Pseudotumor of the lung(2023-01-01) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Automated segmentation of infarct lesions in t1‐weighted mri scans using variational mode decomposition and deep learning(2021-03-02); ; ; Automated segmentation methods are critical for early detection, prompt actions, and immediate treatments in reducing disability and death risks of brain infarction. This paper aims to develop a fully automated method to segment the infarct lesions from T1‐weighted brain scans. As a key novelty, the proposed method combines variational mode decomposition and deep learning-based segmentation to take advantages of both methods and provide better results. There are three main technical contributions in this paper. First, variational mode decomposition is applied as a pre-processing to discriminate the infarct lesions from unwanted non‐infarct tissues. Second, overlapped patches strategy is proposed to reduce the workload of the deep‐learning‐based segmentation task. Finally, a three‐dimensional U‐Net model is developed to perform patch‐wise segmentation of infarct lesions. A total of 239 brain scans from a public dataset are utilized to develop and evaluate the proposed method. Empirical results reveal that the proposed automated segmentation can provide promising performances with an average dice similarity coefficient (DSC) of 0.6684, intersection over union (IoU) of 0.5022, and average symmetric surface distance (ASSD) of 0.3932, respectively. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Automated Bacterial Colony Counting on Agar Plate(2023-01-01) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Optical-based foot plantar pressure measurement with application in human postural balance, gait and recognition analysis(2020-07-01); ; ; Aoyama, HisayukiIn this research, we purposed the design of real-time low-cost marker-free optical-based plantar-pressure measurement with application in human postural control, gait and recognition analysis. The system consists of a series of digital cameras capture installed underneath the acrylic-top platform. Light of LED strip mounted along the side of the acrylic plate deflected by the pressure exerted between the glossy white paper installed in the top of acrylic and the acrylic plate to the digital cameras provides the color-coded plantar pressure image of the subject standing on the platform. The system can provide both static features and dynamic features. Our hybrid system consists of a series of USB cameras aligned under the acrylic-plate walking platform. The mosaic image processing is used to concatenate the captured image to increase the sensing area. Captured the image data in video mode, various dynamic parameters can be derived for further dynamic analysis. The image capturing in one specific frame can be used for static analysis. Application in human-postural measurement, gait analysis, and person identification indicate that our system is an all-in-one system for plantar pressure measurement. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Cry4Aa and Cry4Ba Mosquito-Active Toxins Utilize Different Domains in Binding to a Particular Culex ALP Isoform: A Functional Toxin Receptor Implicating Differential Actions on Target Larvae(2022-10-01); Li, Hui ChunThe three-domain Cry4Aa toxin produced from Bacillus thuringiensis subsp. israelensis was previously shown to be much more toxic to Culex mosquito larvae than its closely related toxin—Cry4Ba. The interaction of these two individual toxins with target receptors on susceptible larval midgut cells is likely to be the critical determinant in their differential toxicity. Here, two full-length membrane-bound alkaline phosphatase (mALP) isoforms from Culex quinquefasciatus larvae, Cq-mALP1263and Cq-mALP1264, predicted to be GPI-linked was cloned and functionally expressed in Spodoptera frugiperda (Sf9) cells as 57- and 61-kDa membrane-bound proteins, respectively. Bioinformatics analysis disclosed that both Cq-mALP isoforms share significant sequence similarity to Aedes aegypti-mALP—a Cry4Ba toxin receptor. In cytotoxicity assays, Sf9 cells expressing Cq-mALP1264, but not Cq-mALP1263, showed remarkably greater susceptibility to Cry4Aa than Cry4Ba, while immunolocalization studies revealed that both toxins were capable of binding to each Cq-mALP expressed on the cell membrane surface. Molecular docking of the Cq-mALP1264-modeled structure with individual Cry4 toxins revealed that Cry4Aa could bind to Cq-mALP1264 primarily through particular residues on three surface-exposed loops in the receptor-binding domain—DII, including Thr<sup>512</sup>, Tyr<sup>513</sup> and Lys<sup>514</sup> in the β10-β11loop. Dissimilarly, Cry4Ba appeared to utilize only certain residues in its C-terminal domain—DIII to interact with such a Culex counterpart receptor. Ala-substitutions of selected β10-β11loop residues (T512A, Y513A and K514A) revealed that only the K514A mutant displayed a drastic decrease in biotoxicity against C. quinquefasciatus larvae. Further substitution of Lys<sup>514</sup> with Asp (K514D) revealed a further decrease in larval toxicity. Furthermore, in silico calculation of the binding affinity change (ΔΔG<inf>bind</inf>) in Cry4Aa-Cq-mALP1264 interactions upon these single-substitutions revealed that the K514D mutation displayed the largest ΔΔG<inf>bind</inf> value as compared to three other mutations, signifying an adverse impact of a negative charge at this critical receptor-binding position. Altogether, our present study has disclosed that these two related-Cry4 mosquito-active toxins conceivably exploited different domains in functional binding to the same Culex membrane-bound ALP isoform—Cq-mALP1264 for mediating differential toxicity against Culex target larvae. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Deep learning-based single-shot phase retrieval algorithm for surface plasmon resonance microscope based refractive index sensing application(2021-12-01); Pechprasarn, SuejitA deep learning algorithm for single-shot phase retrieval under a conventional microscope is proposed and investigated. The algorithm has been developed using the context aggregation network architecture; it requires a single input grayscale image to predict an output phase profile through deep learning-based pattern recognition. Surface plasmon resonance imaging has been employed as an example to demonstrate the capability of the deep learning-based method. The phase profiles of the surface plasmon resonance phenomena have been very well established and cover ranges of phase transitions from 0 to 2π rad. We demonstrate that deep learning can be developed and trained using simulated data. Experimental validation and a theoretical framework to characterize and quantify the performance of the deep learning-based phase retrieval method are reported. The proposed deep learning-based phase retrieval performance was verified through the shot noise model and Monte Carlo simulations. Refractive index sensing performance comparing the proposed deep learning algorithm and conventional surface plasmon resonance measurements are also discussed. Although the proposed phase retrieval-based algorithm cannot achieve a typical detection limit of 10<sup>–7</sup> to 10<sup>–8</sup> RIU for phase measurement in surface plasmon interferometer, the proposed artificial-intelligence-based approach can provide at least three times lower detection limit of 4.67 × 10<sup>–6</sup> RIU compared to conventional intensity measurement methods of 1.73 × 10<sup>–5</sup> RIU for the optical energy of 2500 pJ with no need for sophisticated optical interferometer instrumentation. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Bone mineral density screening system using CMOS-sensor X-ray detector(2021-11-01); This research concerns a design and construction of a bone mineral density (BMD) and bone mineral content (BMC) measurement system based on dual energy x-ray absorptiometry (DEXA). An indirect x-ray detector is designed by optical coupling CMOS sensor with image on the intensifying screen. A dedicated microcontroller x-ray apparatus is used as an x-ray source to cap-ture two energy level x-ray of middle phalanges bone of middle finger. The captured image is processed based on modified Beer-Lambert law to compute bone mineral density. Bone mineral content is also computed by determining the area of the phalanges bone using active contour. The designed bone mineral density (BMD) and bone mineral content (BMC) measurement system is low-cost and hence can be distributed at district hospital for screening purposes of Osteoporosis of the elderly. Compared with BMD measured from commercial model, BMD measurement of our system ac-quires linear relation with R<sup>2</sup> equals 0.969. The mean square error between the normalized BMD value and that of the commercial model is 0.0000981. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Feature-Based Classification of Mild Cognitive Impairment and Alzheimer’s Disease Based on Optical Coherence Tomographic Angiographic Image(2024-08-01);