Pintavirooj, Chuchart

Preferred name

Alternative Name

Pintavirooj, C.

Pintavirooj, Chuchat

Main Affiliation

School of Engineering

chuchart.pi@kmitl.ac.th

Now showing 1 - 10 of 17

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Basic investigation of breast cancer detection in early stage using microwave radiation: Finite element analysis approach
(2011-12-01)
Sanpanich, A.
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Phasukkit, P.
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Tungjitkusolmun, S.
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Pintavirooj, C.
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Wongtrairat, W.
One of the main problem which threatening health in middle-aged women around the world is breast cancer. Not only a physical painfulness but also including her own family and victim relatives who suffering from this unavoidable pity fate. To detect those cancerous tumors as in an earlier stage as possible seem to be the best way to handle with this hazard. Besides from x-rays mammography and a conventional diagnostic ultrasound, microwave radiation tomography technique is a promising method to investigate any abnormality forming in her mammalian gland. In this paper, we propose a simulation of microwave radiation using a finite element method (FEM) of our modified imaging setup system for female breast cancer diagnosis. By using FEM, we propose a preliminary study of microwave breast cancer detection from a patch antenna propagation in 3D tissue space approaching. In term of wave penetration, voluminous 3D distribution geometry of electrical field in nonhomogenous simple breast phantom model was presented. These simulations not only show a promising result but also encourage us to develop a real imaging setup system in the near future. © 2011 IEEE.
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Combined medical imaging with CFD analysis for application of diagnostic and treatment planning: The case study of human nasal airflow simulation based on CT imaging
(2009-01-01)
Hemtiwakorn, Khaisang
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Phoocharoen, Niwat
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Tungjitkusolmun, Supan
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Mahasittiwat, Visan
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Sangworasil, Manas
The previous methods of human airflow measurement such as rhinomanometry or acoustic rhinometry could not visualize the airflow and calculated the velocity magnitude in specific region of nasal cavity. Thus, this study proposes the combination of CT and CFD analysis of nasal airflow simulation in normal human breathing. This method can demonstrate the airflow direction, and also calculate the velocity magnitude inside the nasal cavity. The processes of this study are segmentation, meshing, solving, and post-processing. Firstly, Mimic 10.01 software was used to segment the nasal cavity. Secondly, Pro-STAR/amm software was used to generate trimmed mesh of 338, 496 elements. Finally, computational grid model was imported to STAR-CD version 3.26 for numerical computation, and visualize the solution by post-processing. The result shows that velocity magnitude of airflow is greatest in nasal valve area which is the narrowest area of the human nose. Also, the flow commonly pass through the main nasal passage and middle meatus areas of nose. Experimental validation will be reported in the further publication. In conclusion, this study is the important begining of an applied CFD analysis with medical imaging. CT imaging combines with CFD analysis could be useful for rhinologist as a nose function evaluation technique. Moreover, the applications of this method could be utilized in a wide range of research topics, especially development of diagnostic and treatment planning techniques.
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Message from Technical Program Chair
(2023-01-01)
Pintavirooj, Chuchart
;
Tungjitkusolmun, Supan
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Kiattsin, Supaporn
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Thaijiam, Chanchai
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Yoshino, Kohzoh
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Patient-specific aided surgery approach of deviated nasal septum using computational fluid dynamics
(2015-05-01)
Hemtiwakorn, Khaisang
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Mahasitthiwat, Visan
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Tungjitkusolmun, Supan
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Hamamoto, Kazuhiko
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Pintavirooj, Chuchart
In treating a patient with deviated nasal septum (DNS), a surgeon draws up a surgical plan based on the patient's rhinomanometry outcomes and self-assessment of nose conditions, e.g. the nasal obstruction septoplasty effectiveness (NOSE) score. However, the procedure fails to localize the DNS and determine the nose's aerodynamic effects. This paper proposes a DNS-aided surgery approach using computational fluid dynamics (CFD) and computed tomography (CT) techniques consisting of three main processes: preoperative, presurgical planning, and postoperative processes. The healthy baseline refers to a benchmark consisting of five subjects without DNS and nasal airway obstructions. To assess the possibility of using the CFD-CT-aided surgery approach as a presurgical planning tool in the DNS operation, comparative tests were carried out with DNS patient #1, who received a conventional nasal surgery without the proposed presurgical planning. Although DNS patient #1's surgical outcome was relatively satisfying to the patient, evaluating from the reduction of the NOSE score the conventional surgical method could induce an excessive excision of nasal airway, resulting in water loss in the nasal mucosa and a large reduction in airflow velocity. In addition, the postoperative nasal resistance measured by a rhinomanometer was not acceptable to the surgeon. Virtual surgery using the CFD-CT approach performed after surgery could suggest suitable patient-specific components of nasal operation with predictable results. Subsequently, implementation of the proposed CFD-CT approach in aid of DNS surgery was performed in DNS patient #2. The benefits of the CFD-CT-aided surgery approach were determined based on the pre- and postoperative outcomes (i.e. nasal geometric data and nasal airflow patterns), NOSE scores, and rhinomanometric data of DNS patient #2, which were compared against those of the healthy baseline benchmark. The CFD-CT approach could assist the surgeon to localize the DNS and determine the defective nasal tissues to be removed. The actual postoperative outcomes were clinically acceptable to the surgeon and DNS patient #2. It is evident that the CFD-CT-aided surgery approach is suitable for and applicable to surgery of DNS patients with small variability from the presurgical planning stage.
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Automated segmentation of infarct lesions in t1‐weighted mri scans using variational mode decomposition and deep learning
(2021-03-02)
Paing, May Phu
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Tungjitkusolmun, Supan
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Bui, Toan Huy
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Visitsattapongse, Sarinporn
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Pintavirooj, Chuchart
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.
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Automatic detection of pulmonary nodules using three-dimensional chain coding and optimized random forest
(2020-04-01)
Paing, May Phu
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Hamamoto, Kazuhiko
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Tungjitkusolmun, Supan
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Visitsattapongse, Sarinporn
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Pintavirooj, Chuchart
The detection of pulmonary nodules on computed tomography scans provides a clue for the early diagnosis of lung cancer. Manual detection mandates a heavy radiological workload as it identifies nodules slice-by-slice. This paper presents a fully automated nodule detection with three significant contributions. First, an automated seeded region growing is designed to segment the lung regions from the tomography scans. Second, a three-dimensional chain code algorithm is implemented to refine the border of the segmented lungs. Lastly, nodules inside the lungs are detected using an optimized random forest classifier. The experiments for our proposed detection are conducted using 888 scans from a public dataset, and achieves a favorable result of 93.11% accuracy, 94.86% sensitivity, and 91.37% specificity, with only 0.0863 false positives per exam.
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Opened-tip applicator and ex vivo experimental results for microwave breast cancer ablation
(2012-11-26)
Sanpanich, A.
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Kajornpredanon, Y.
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Phasukkit, P.
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Tungjitkusolmun, S.
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Pintavirooj, C.
Breast cancer is one of the main health hazard that threatening women life all over the world. Not only her own daily life, but also her own family whom suffering from this poor fate. Besides from a breast resection, microwave ablation is also another effective therapeutic technique for glandular tissue cancer treatment due to its minimal invasive maneuver. In this paper, we propose a study of an opened-tip applicator ablation for breast cancer therapy. The investigation was preliminary performed by using finite element method to analyze a characteristic of antenna and to simulate a 2.45 GHz electromagnetic wave phenomenon in living tissue then following by ex vivo experiment with female swine breast. In term of FEM simulation, full 3D distribution pattern of SAR, temperature and also estimated destructive tissue area in a complicated CAD model of cancerous breast was analyzed. Real ablation with an ultrasound-guided applicator insertion was implemented to confirm an effective result. This study not only shows a promising result but also encourage us to develop an advance microwave ablation system in near future. © 2012 IEEE.
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Automatic detection of mediastinal lymph nodes using 3D convolutional neural network
(2019-09-16)
Paing, May Phu
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Pintavirooj, Chuchart
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Tungjitkusolmun, Supan
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Win, Kyi Pyar
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Hamamoto, Kazuhiko
Mediastinal lymph nodes are one of the most critical factors to identify the clinical stages of lung cancer. As the lymph nodes are low in attenuation and cluttering with various shapes and sizes, manual detection is usually error-prone and effort-intensive. This paper introduces a method for automatic detection of mediastinal lymph nodes by proposing three significant contributions. First, we constraint the detection area, mediastinal region, using greylevel thresholding. Next, we apply the watershed method and hessian eigenvalues to separate a cluster of lymph nodes. Finally, we build a three-dimensional convolutional neural network (3D CNN) to distinguish the actual lymph nodes from other false lesions. Our experiment is conducted using 70 CT exams containing 314 lymph nodes and achieved a favorable result with 94 % detection rate.
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3D finite element analysis for varicose vein therapy by using microwave ablation
(2012-12-01)
Prasantamrongsiri, S.
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Phasukkit, P.
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Pintavirooj, C.
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Tungjitkusolmun, S.
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Sanpanich, A.
This paper presents three-dimensional finite element method for analyze a varicose vein microwave ablation. Varicose vein can contract by using heat from microwave ablation. Because of varicose vein patients have leg pain from long time standing, and do a lot of activities. Symptoms have influenced the daily life of patients. We study method for varicose vein therapy by using microwave ablation. Because of this method is easy to use for varicose vein therapy. In this research work, we propose simulation varicose vein that varicose vein is inserted with antenna into blood vessel. Simulation method delivers microwave to antenna inserted in varicose vein. For this reason, varicose vein is contract. Finite element analysis can apply in treatment planning and show temperature distribution and specific absorption rate (SAR) distribution for contract of varicose vein characteristic by using microwave therapy. And the doctor can be use the data for treat in future. ©2012 IEEE.
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Design and Development of Equipment Wrist and Forearm Physical Therapeutic in Elderly Persons
(2019-01-10)
Phetnuam, Siriphan
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Pintavirooj, C.
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Tungjitkusolmun, Supan
This paper describes design game and development exercise device for wrist and forearm of elder. In 2009, the number of the senior population has increased rapidly. The society has entered into an aging society. And senior population ages more than 80 years old have sickness, Organ degeneration and someone have a disability. Exercise is one of the important things that can keep the elderly have good health and reduce reliance should others. However, the senior population should not over the exercise. The design game and development of equipment for exercise wrist and forearm to the elderly person. To encourage older people to exercise more. Also, this device can apply to physical therapy for wrist and forearm of the patient. Results of goniometry, EMG and total earning score from playing games are increased due to more flexible effect to muscle after playing games. Furthermore, an extension of equipment and games will be developed for more exercise or physical therapy in other positions.

Pintavirooj, Chuchart

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