Saowapak S. Thongvigitmanee

Radiation dose and accuracy analysis of newly developed cone-beam CT for dental and maxillofacial imaging

Cone-beam computed tomography (CBCT) has become increasingly popular in dental and maxillofacial imaging due to its accurate 3D information, minimal radiation dose, and low machine cost. In this paper, we have proposed the newly developed CBCT scanner, called DentiiScan. Our gantry system consisting of a cone-beam X-ray source and an amorphous silicon flat panel detector is rotated around a patients head. With the large area detector, only a single rotation is needed to reconstruct the field-of-view area from chin to eyes and our reconstructed algorithm based on GPU calculation is about 30 times faster than the CPU-based algorithm. The radiation dose was measured and compared to other dental and medical CT machines. The absorbed radiation dose from our proposed CBCT machine is significantly low. In addition, geometric accuracy was analyzed when the test object was scanned at the normal position as well as the inclined position. The results from three observers repeated for five times confirm that the machine can produce reconstructed images with high accuracy.

Experiment-based scatter correction for cone-beam computed tomography using the statistical method

Scatter signals in cone-beam computed tomography (CBCT) cause a significant problem that degrades image quality of reconstructed images, such as inaccuracy of CT numbers and cupping artifacts. In this paper, we will present an experiment-based scatter correction method by pre-processing projection images using a statistical model combined with experimental kernels. The convolution kernels are estimated by using different thickness of PMMA plates attached to a beam stop lead sheet such that the scatter signal values can be measure in the shadow area of the projection images caused by the lead sheet. The scatter signal values of different thickness levels can be measured in the shadow area of projection images caused by the lead sheet. Then, the projection images are convolved with the kernels that are derived from the actual measurement of scatter signals in PMMA plates. Finally, the primary signals can be estimated using the maximum likelihood expectation maximization method. Experimental results by using the proposed method show that the quality of the reconstruction images is significantly improved. The CT numbers become more accurate and the cupping artifact is reduced.

CT Image Management and Communication Services

Nowadays computed tomography (CT) becomes very popular and useful in both medical and dental areas. Due to the standard DICOM (Digital Imaging and Communications in Medicine) file format of CT images containing special headers of image, patient and device information, dentists or specialists require to use DICOM viewer software to display those images. After acquiring a CT scan, a traditional way to transfer the CT images from the CT workstation to another place is by having someone carry a CD containing DICOM images with or without viewer software. To accommodate or speed up this process, especially when an interpreting radiologist and a referring dentist are in different places, we have developed a CT image management and communication service process which provides online dental image management as well as viewer software available for the invocation by web and mobile applications. Our system can support image stream, online CT scan request and image download services. The web and mobile applications allow dentists or specialists to view and analyze images at anywhere anytime. This complete system would gain high benefits to not only a dental CT service center but also other medical imaging service centers as well.

Object Tracking for Laparoscopic Surgery Using theAdaptive Mean-Shift Kalman Algorithm

this paper, we propose the adaptive mean-shift Kalman tracking algorithm based on the mean-shift algorithm and the Kalman filter for tracking a laparoscopic instrument in laparoscopic surgery. With an iterative update of the target candidate in the mean-shift process, the proposed algorithm has improved the tracking performance over a typical mean-shift algorithm. In addition, the Kalman filter is employed to enhance the chance of tracking accuracy, especially when the object disappears from the scene. We tested the tracking performance of our proposed algorithm through simulated videos and real laparoscopic surgery videos. From all experimental results, the proposed algorithm can locate the target object correctly even when the size and the shape of the target have been changed. In the difficult situation when the target is hiding behind an obstacle, this algorithm can still track the target object correctly after it comes out. In addition, the proposed algorithm can be applied to locate different types of laparoscopic instruments.

X-Ray Scatter Correction on Soft Tissue Images for Portable Cone Beam CT

Soft tissue images from portable cone beam computed tomography (CBCT) scanners can be used for diagnosis and detection of tumor, cancer, intracerebral hemorrhage, and so forth. Due to large field of view, X-ray scattering which is the main cause of artifacts degrades image quality, such as cupping artifacts, CT number inaccuracy, and low contrast, especially on soft tissue images. In this work, we propose the X-ray scatter correction method for improving soft tissue images. The X-ray scatter correction scheme to estimate X-ray scatter signals is based on the deconvolution technique using the maximum likelihood estimation maximization (MLEM) method. The scatter kernels are obtained by simulating the PMMA sheet on the Monte Carlo simulation (MCS) software. In the experiment, we used the QRM phantom to quantitatively compare with fan-beam CT (FBCT) data in terms of CT number values, contrast to noise ratio, cupping artifacts, and low contrast detectability. Moreover, the PH3 angiography phantom was also used to mimic human soft tissues in the brain. The reconstructed images with our proposed scatter correction show significant improvement on image quality. Thus the proposed scatter correction technique has high potential to detect soft tissues in the brain.

Automatic dental arch detection and panoramic image synthesis from CT images

Due to accurate 3D information, computed tomography (CT), especially cone-beam CT or dental CT, has been widely used for diagnosis and treatment planning in dentistry. Axial images acquired from both medical and dental CT scanners can generate synthetic panoramic images similar to typical 2D panoramic radiographs. However, the conventional way to reconstruct the simulated panoramic images is to manually draw the dental arch on axial images. In this paper, we propose a new fast algorithm for automatic detection of the dental arch. Once the dental arch is computed, a series of synthetic panoramic images as well as a ray-sum panoramic image can be automatically generated. We have tested the proposed algorithm on 120 CT axial images and all of them can provide the decent estimate of the dental arch. The results show that our proposed algorithm can mostly detect the correct dental arch.

Adaptive Mean-Shift Kalman Tracking of Laparoscopic Instruments

Laparoscopic surgery becomes increasingly popular due to high benefits to both surgeon and patients. In this paper, we propose the adaptive mean-shift Kalman tracking algorithm based on the mean-shift algorithm and the Kalman filter for tracking a laparoscopic instrument in laparoscopic surgery. An iterative update of the target candidate in the mean-shift process can improve the tracking performance over a typical mean-shift algorithm. In addition, the Kalman filter is employed to enhance the chance of tracking accuracy, especially when the object disappears from the scene. In this study, we tested the tracking performance of our proposed algorithm by using the different situations from simulated videos. Our experimental results show that the proposed algorithm can locate the target object correctly even when the size and the shape of the target have been changed. In the difficult situation when the target is hiding behind an obstacle, this algorithm can still track the target object correctly after it becomes apparent. Therefore, this proposed algorithm can be used for locating the tip of the laparoscopic instrument in real laparoscopic surgery. the color tracking algorithm to control a robotic laparoscope instead of using human; however, this method cannot track many types of instruments. Casals et al. (3) introduced feature tracking algorithm based on shape information of a surgical instrument; however, it works only with a specific surgical instrument. Lee et al. (4) proposed a color and shape tracking algorithm by using the contour of the surgical instrument. This algorithm worked well in the normal situation, but not when the instrument is blocked by some obstacles. Wei et al. (5) presented a simple algorithm for tracking target features. However, this algorithm is based on the artificial color marks attached to a surgical instrument, but there are many disadvantages, such as sterilization of the mark on the surgical instrument and its convenience in the real practice. Because of some limitations in previous methods, in this paper, we propose a new object tracking algorithm to track the laparoscopic instrument called the adaptive mean-shift Kalman algorithm (6), which is based on the mean-shift algorithm (7) and the Kalman filter (8).In this algorithm, the size of the target candidate can be adjusted during tracking processes to increase the chance of tracking. We simulated videos with different scenarios to test the performance of our proposed algorithm. Furthermore, the proposed algorithm is intended to use for controlling our new laparoscopic-holder assistant robot (9-10) and tracking the tip of its instruments in laparoscopic surgery.

Quantitative Performance Evaluation of Mobile Cone-Beam CT for Head and Neck Imaging

Cone-beam computed tomography (CBCT) has become increasingly popular in dental and maxillofacial imaging due to its accurate 3D information, minimal radiation dose, and low machine cost. In this paper, we propose the newly developed mobile CBCT scanner which combines the benefits of CBCT and mobility to extend its applications to head and neck imaging and allow faster access to a patient at various clinical sites. With the large area detector, only a single rotation is needed to reconstruct the field-of-view of almost the entire head. Our filtered back-projection reconstruction and artifact reduction algorithms were based on a graphics processing unit to speed up the calculations. The quantitative performance was evaluated in terms of radiation doses and image quality. The radiation doses were measured using both CT dose index and dose area product (DAP) and compared with other CBCT and multi-slice CT (MSCT) machines. Then, we analyzed image quality using the standard cone-beam phantom. The effective doses radiated from the proposed mobile CBCT machine were within the range of 0.1–0.2 mSv, while the normalized DAP measurements were within the range of 46–144 mGy cm2, which are significantly below the achievable dose of 250 mGy cm2. The overall image quality of the proposed scanner was mostly comparable to other MSCT and CBCT scanners. Geometric accuracy of the reconstructed images provided the errors less than 0.16 mm or 0.12%. Due to low radiation dose, high accuracy and adequate image quality as compared to others, the proposed mobile CBCT has high potential for diagnosis and treatment planning in head and neck applications.

A Simple Scatter Reduction Method in Cone-Beam Computed Tomography for Dental and Maxillofacial Applications Based on Monte Carlo Simulation

The quality of images obtained from cone-beam computed tomography (CBCT) is important in diagnosis and treatment planning for dental and maxillofacial applications. However, X-ray scattering inside a human head is one of the main factors that cause a drop in image quality, especially in the CBCT system with a wide-angle cone-beam X-ray source and a large area detector. In this study, the X-ray scattering distribution within a standard head phantom was estimated using the Monte Carlo method based on Geant4. Due to small variation of low-frequency scattering signals, the scattering signals from the head phantom can be represented as the simple predetermined scattering signals from a patients head and subtracted the projection data for scatter reduction. The results showed higher contrast and less cupping artifacts on the reconstructed images of the head phantom and real patients. Furthermore, the same simulated scattering signals can also be applied to process with higher-resolution projection data.

Automatic initialization for active contour model in breast cancer detection utilizing the integration of ultrasonography image modalities

Breast cancer is the most common category of cancers in woman around the world. Ultrasonography imaging modalities (US) are highly recommended for breast cancer examining due to their sensitivity, specificity, cost-effective, accessibility, portability, comfort, as well as non-invasive tool. In addition, an integration of a conventional US and its adjunct modalities which is Power Doppler has been proved for reducing fault-positive in breast cancer diagnosis. The combination of conventional US and Power Doppler also increases sensitivity and specificity in a woman who has dense breast. Hence, the integration of US-based imaging modalities would also benefit in medical image processing such as a breast cancer segmentation. An affective method for medical image segmentation, active contour model has been widely used for decades. A crucial stage that affect the performance of the model is initialization. This paper proposed a novel method, an automatic initialization for parametric active contour model. It is significant difference from previous methods that focus on vector flow analysis. Our method estimates an appropriate initial contour by utilizing the integration of conventional US and Power Doppler. Examples and comparison with a state-of-the-art method for automatic initialization are demonstrated showing better performance for initialization.