• Journal of Biomedical Engineering Research
• /
• v.26 no.4
• /
• pp.185-191
• /
• 2005

In this paper, we proposed a downscaled 3D object technique using medical images for telediagnostic use. The proposed system consisted of downscaling/thresholding processes for building a downscaled 3D object and a process for obtaining 2D images at specific angles for diagnosis support. We used 80 slices of Digital Imaging and Communication in Medicine(DICOM) CT images as sample images and the platform-independent Java language for the experiment. We confirmed that the total image set size and transmission time of the original DICOM image set using a down-scaled 3D object decreased approximately $99\%\;and\;98.41\%,$ respectively. With additional studies, the proposed technique obtained from these results will become useful in supporting diagnosis for home and hospital care.

• Proceedings of the KOSOMBE Conference
• /
• v.1998 no.11
• /
• pp.113-114
• /
• 1998

In this paper, visualization of Visible Human data offered by NLM(National Library of Medicine) is performed using $VTK^{TM}$. Computed Tomography Data set(axial, $587\times341\times256$, and the distance between slices 1mm) is used throughout the study. Before the actual visualization routine, 8 bit-reader class of VTK is developed to transform CT data to VTK dataset. After that, the visualization procedures are done to display 3D image on PC. VTK is freeware, not a commercial software. The results of VTK show relatively good image quality and slower processing time compared with the commercial softwares like IAP, IDL, AVS. Thus if processing time is not the critical factor, VTK is worthy to be used in visualization of the medical images.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.5
• /
• pp.331-337
• /
• 2023

In this paper, we propose a deep learning model to detect lumbar 3 (L3) CT images to determine the occurrence and degree of sarcopenia. In addition, we would like to propose an optimization technique that uses oversampling ratio and class weight as design parameters to address the problem of performance degradation due to data imbalance between L3 level and non-L3 level portions of CT data. In order to train and test the model, a total of 150 whole-body CT images of 104 prostate cancer patients and 46 bladder cancer patients who visited Gangneung Asan Medical Center were used. The deep learning model used ResNet50, and the design parameters of the optimization technique were selected as six types of model hyperparameters, data augmentation ratio, and class weight. It was confirmed that the proposed optimization-based L3 level extraction model reduced the median L3 error by about 1.0 slices compared to the control model (a model that optimized only 5 types of hyperparameters). Through the results of this study, accurate L3 slice detection was possible, and additionally, we were able to present the possibility of effectively solving the data imbalance problem through oversampling through data augmentation and class weight adjustment.

• Journal of the Korea Computer Graphics Society
• /
• v.2 no.1
• /
• pp.77-85
• /
• 1996

Using a series of medical tomograms, we can reconstruct internal organs or other objects of interest and generate 3-D images. It is generally accepted that the axial resolution determined by two sequential image slices is lower than the planar resolution in one image slices. Therefore, various methods of interpolation were developed for an accurate display of reconstructed images. In this paper, a new algorithm for 3-D reconstruction of the medical images such as MRI and X-ray CT is suggested. The algorithm is shape-based and utilizes parts of the gray-level information. We extend the conventional shape-based interpolation of the binary images to the gray-scale images using the shortest distance map. Using this new algorithm, We could reduce the execution time for interpolation while keeping similar high quality of the reconstructed images with reduced execution time and is applicable to the various medical tomograms.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.14 no.2
• /
• pp.110-116
• /
• 2010

Purpose: The X-ray attenuation coefficient based on CT images is used for attenuation correction in PET/CT. The polychromatic X-ray beam can introduce beam-hardening artifact on CT images. The aims of the study were to evaluate the effect of dental metal prostheses in phantom and patients on apparent tracer activity measured with PET/CT when using CT attenuation correction. Materials and Methods: 40 normal patients (mean age $54{\pm}12$) was scanned between Jan and Feb 2010. NEMA(National Electrical Manufactures Association) PET $Phantom^{TM}$ (NU2-1994) was filled with $^{18}F$-FDG injected into the water that insert implant and metal prostheses dental cast. Region of interest were drawn in non-artifact region, bright steak artifact region and dark streak artifact region on the same transaxial CT and PET slices. Patients and phantom with dental metal prostheses and dental implant were evaluated the change rate of CT Number and $SUV_{mean}$ in PET/CT. A paired t-test was performed to compare the ratio and the difference of the calculated values. Results: In patients with dental metal prostheses, $SUV_{mean}$ was reduced 19.64% (p<0.05) in the non-steak artifact region than the brightstreak artifact region whereas was increased 90.1% (p>0.05) in the non-steak artifact region than the dark streak artifact region. In phantom with dental metal prostheses, $SUV_{mean}$ was reduced 18.1% (p<0.05) in the non-steak artifact region than the bright streak artifact region whereas was increased 18.0% (p>0.05) in the non-steak artifact region than the dark streak artifact region. In patients with dental implant, $SUV_{mean}$ was increased 19.1% (p<0.05) in the non-steak artifact region than the bright streak artifact region whereas was increased 96.62% (p>0.05) in the non-steak artifact region than the dark streak artifact region. In phantom with dental implant, $SUV_{mean}$ was increased 14.4% (p<0.05) in the non-steak artifact region than the bright streak artifact region whereas was increased 7.0% (p>0.05) in the non-steak artifact region than the dark streak artifact region. Conclusion: When CT is used for attenuation correction in patients with dental metal prostheses, 19.1% reduced $SUV_{mean}$ is anticipated in the dark streak artifact region on CT images. The dark streak artifacts of CT by dental metal prostheses may cause false negative finding in PET/CT. We recommend that the non-attenuation corrected PET images also be evaluated for clinical use.

• Progress in Medical Physics
• /
• v.9 no.4
• /
• pp.201-206
• /
• 1998

IMRT optimization method on multiple slice has been developed by using gradient based algorithm. On about 10-30 CT slices including treatment region of a patient, dose optimization has been performed slice by slice to meet the condition that each organ should be exposed below maximum tolerable doses and that the tumor dose within the range of 100$\pm$5 %. Field size was limited to 8$\times$8 cm$^2$ and in this condition, beam divergence was not taken into account to calculate dose distribution. Total dose distribution was calculated by superposing each beamlet whose dose distribution had been precalculated. In order to investigate beam number dependency, dose optimization was performed for one, three, five, seven, and nine coplanar beams and then each optimization index was evaluated. It is found that optimization time was proportional to number of slices to be optimized, and the most efficient plan was obtained from the case of three-to-seven incident beams with respect to calculation time and optimization index. In conclusion, dose optimization of multiple slice was able to be obtained by repeating dose optimization of single slice under condition that the beam size is not too large to ignore beam divergence. And it turns out that result of dose optimization was so sensitive to the position of isocenter that some method to optimize isocenter position is needed to improve it.

• Korean Journal of Radiology
• /
• v.24 no.8
• /
• pp.807-820
• /
• 2023

Objective: To assess whether computed tomography (CT) conversion across different scan parameters and manufacturers using a routable generative adversarial network (RouteGAN) can improve the accuracy and variability in quantifying interstitial lung disease (ILD) using a deep learning-based automated software. Materials and Methods: This study included patients with ILD who underwent thin-section CT. Unmatched CT images obtained using scanners from four manufacturers (vendors A-D), standard- or low-radiation doses, and sharp or medium kernels were classified into groups 1-7 according to acquisition conditions. CT images in groups 2-7 were converted into the target CT style (Group 1: vendor A, standard dose, and sharp kernel) using a RouteGAN. ILD was quantified on original and converted CT images using a deep learning-based software (Aview, Coreline Soft). The accuracy of quantification was analyzed using the dice similarity coefficient (DSC) and pixel-wise overlap accuracy metrics against manual quantification by a radiologist. Five radiologists evaluated quantification accuracy using a 10-point visual scoring system. Results: Three hundred and fifty CT slices from 150 patients (mean age: 67.6 ± 10.7 years; 56 females) were included. The overlap accuracies for quantifying total abnormalities in groups 2-7 improved after CT conversion (original vs. converted: 0.63 vs. 0.68 for DSC, 0.66 vs. 0.70 for pixel-wise recall, and 0.68 vs. 0.73 for pixel-wise precision; P < 0.002 for all). The DSCs of fibrosis score, honeycombing, and reticulation significantly increased after CT conversion (0.32 vs. 0.64, 0.19 vs. 0.47, and 0.23 vs. 0.54, P < 0.002 for all), whereas those of ground-glass opacity, consolidation, and emphysema did not change significantly or decreased slightly. The radiologists' scores were significantly higher (P < 0.001) and less variable on converted CT. Conclusion: CT conversion using a RouteGAN can improve the accuracy and variability of CT images obtained using different scan parameters and manufacturers in deep learning-based quantification of ILD.

• Journal of Korean Neurosurgical Society
• /
• v.38 no.4
• /
• pp.265-268
• /
• 2005

Objective : With the increasing popularity of pedicle screw fixation devices for several indications, the safety and reliability of screw insertion in the small pedicle has become a major issue. Many studies have investigated the accuracy of screw placement after pedicle screw fixation using various method. The reported displacement rates have been very different. The purpose of the study is to investigate the proper placement of pedicle screw insertion in the lumbar spine on 26 consecutive patients. Methods : Between September and December 2003, 26 consecutive patients [16women and 10men] were analyzed after transpedicular screw fixation of the lumbar and lumbosacral spine. After pedicle screw fixation in this study, 2-mm slices of CT scan were performed in all patients to detect caudal and cranial deviation of screw and medial and lateral deviation. Pedcile screw placement related complication was evaluated clinically. Results : A total of 144 inserted pedicle were analyzed in 26patients, and 58pedicle screws [40.3%] were detected to be improper placement. There were 14level [9.0%] of caudal or cranial deviation and 44level [30.6%] of medial or lateral deviation to the pedicle. Extra-pedicle placement was found on 4levels [2.7%] with only lease of neurologic injury. Conclusion : Proper screw placement, though complication rate is low, is important not only for clinical symptom but also for biomechanics. Further study for screw placement related biomechanical changes is needed.

• Journal of Korean Neurosurgical Society
• /
• v.49 no.2
• /
• pp.107-111
• /
• 2011

Objective : The aim of this study was to evaluate the utility of volume-rendered helical computerized tomography (CT) angiography focusing tracheostomy tube and innominate artery for prevention of tracheoinnominate artery fistula. Methods : The authors retrospectively analyzed 22 patients with tracheostomy who had checked CT angiography. To evaluate the relationship between tracheostomy tube and innominate artery, we divided into three categories. First proximal tube position based on cervical vertebra, named "tracheostomy tube departure level (TTDL)". Second, distal tube position and course of innominate artery, named "tracheostomy tube-innominate artery configuration (TTIC)". Third, the gap between the tube and innominate artery, named "tracheostomy tube to innominate artery gap (TTIG)". The TTDL/TTIC and TTIG are based on 3-dimensional (3D) reconstruction around tracheostomy and enhanced axial slices of upper chest, respectively. Results : First, mean TTDL was $6.8{\pm}0.6$. Five cases (23%) were lower than C7 vertebra. Second, TTIC were remote to innominate artery (2 cases; 9.1 %), matched with it (14 cases; 63.6%) or crossed it (6 cases; 27.3%). Only 9% of cases were definitely free from innominate artery injury. Third, average TTIG was $4.3{\pm}4.6$ mm. Surprisingly, in 6 cases (27.3%), innominate artery, trachea wall and tracheostomy tube were tightly attached all together, thus have much higher probability of erosion. Conclusion : If low TTDL, match or crossing type TTIC with reverse-L shaped innominate artery, small trachea and thin TTIG are accompanied all together, we may seriously consider early plugging and tube removal.

• The Korean Journal of Nuclear Medicine
• /
• v.38 no.4
• /
• pp.318-324
• /
• 2004

Purpose: Philips GEMINI is a newly introduced whole-body GSO PET/CT scanner. In this study, performance of the scanner including spatial resolution, sensitivity, scatter fraction, noise equivalent count ratio (NECR) was measured utilizing NEMA NU2-2001 standard protocol and compared with performance of LSO, BGO crystal scanner. Methods: GEMINI is composed of the Philips ALLEGRO PET and MX8000 D multi-slice CT scanners. The PET scanner has 28 detector segments which have an array of 29 by 22 GSO crystals ($4{\times}6{\times}20$ mm), covering axial FOV of 18 cm. PET data to measure spatial resolution, sensitivity, scatter fraction, and NECR were acquired in 3D mode according to the NEMA NU2 protocols (coincidence window: 8 ns, energy window: $409[\sim}664$ keV). For the measurement of spatial resolution, images were reconstructed with FBP using ramp filter and an iterative reconstruction algorithm, 3D RAMLA. Data for sensitivity measurement were acquired using NEMA sensitivity phantom filled with F-18 solution and surrounded by $1{\sim}5$ aluminum sleeves after we confirmed that dead time loss did not exceed 1%. To measure NECR and scatter fraction, 1110 MBq of F-18 solution was injected into a NEMA scatter phantom with a length of 70 cm and dynamic scan with 20-min frame duration was acquired for 7 half-lives. Oblique sinograms were collapsed into transaxial slices using single slice rebinning method, and true to background (scatter+random) ratio for each slice and frame was estimated. Scatter fraction was determined by averaging the true to background ratio of last 3 frames in which the dead time loss was below 1%. Results: Transverse and axial resolutions at 1cm radius were (1) 5.3 and 6.5 mm (FBP), (2) 5.1 and 5.9 mm (3D RAMLA). Transverse radial, transverse tangential, and axial resolution at 10 cm were (1) 5.7, 5.7, and 7.0 mm (FBP), (2) 5.4, 5.4, and 6.4 mm (3D RAMLA). Attenuation free values of sensitivity were 3,620 counts/sec/MBq at the center of transaxial FOV and 4,324 counts/sec/MBq at 10 cm offset from the center. Scatter fraction was 40.6%, and peak true count rate and NECR were 88.9 kcps @ 12.9 kBq/mL and 34.3 kcps @ 8.84 kBq/mL. These characteristics are better than that of ECAT EXACT PET scanner with BGO crystal. Conclusion: The results of this field test demonstrate high resolution, sensitivity and count rate performance of the 3D PET/CT scanner with GSO crystal. The data provided here will be useful for the comparative study with other 3D PET/CT scanners using BGO or LSO crystals.