Yong-Yeon Jeong

Automatic liver segmentation for volume measurement in CT Images

Computed tomography (CT) images have been widely used for diagnosis of liver disease and volume measurement for liver surgery or transplantation. Automatic liver segmentation and volume measurement based on the segmentation are the most essential parts in computer-aided diagnosis for liver CT as well as computer-aided surgery. However, liver segmentation, in general, has been performed by outlining the medical image manually or segmenting CT images semi-automatically because surface features of the liver and partial-volume effects make automatic discrimination from other adjacent organs or tissues very difficult. Accordingly, in this paper, we propose a new approach to automatic segmentation of the liver for volume measurement in sequential CT images. Our method analyzes the intensity distribution of several abdominal CT samples and exploits a priori knowledge, such as CT numbers and location of the liver to identify coherent regions that correspond to the liver. The proposed scheme utilizes recursively morphological filter with region-labeling and clustering to detect the search range and to generate the initial liver contour. In this search range, we deform liver contour using the labeling-based search algorithm following pattern features of the liver contour. Lastly, volume measurement is automatically performed on the segmented liver regions. The experimental measurement of area and volume is compared with those using manual tracing method as a gold standard by the radiological doctors, and demonstrates that this algorithm is effective for automatic segmentation and volume measurement method of the liver.

Despeckling of medical ultrasound images using Daubechies complex wavelet transform

The paper presents a novel despeckling method, based on Daubechies complex wavelet transform, for medical ultrasound images. Daubechies complex wavelet transform is used due to its approximate shift invariance property and extra information in imaginary plane of complex wavelet domain when compared to real wavelet domain. A wavelet shrinkage factor has been derived to estimate the noise-free wavelet coefficients. The proposed method firstly detects strong edges using imaginary component of complex scaling coefficients and then applies shrinkage on magnitude of complex wavelet coefficients in the wavelet domain at non-edge points. The proposed shrinkage depends on the statistical parameters of complex wavelet coefficients of noisy image which makes it adaptive in nature. Effectiveness of the proposed method is compared on the basis of signal to mean square error (SMSE) and signal to noise ratio (SNR). The experimental results demonstrate that the proposed method outperforms other conventional despeckling methods as well as wavelet based log transformed and non-log transformed methods on test images. Application of the proposed method on real diagnostic ultrasound images has shown a clear improvement over other methods.

Acute gastrointestinal bleeding: contrast-enhanced MDCT

With the introduction of multidetector row computed tomography (MDCT), CT is being considered a potential diagnostic method for patients with acute gastrointestinal (GI) bleeding. On arterial phase MDCT images, active GI bleeding is typically identified as a focal area of high attenuation within the bowel lumen, which represents a collection of contrast material that has been extravasated in association with arterial bleeding. Additional CT findings suggestive of acute GI bleeding are focal dilatation of fluid-filled bowel segment noted on contrast-enhanced CT and acute hematoma on unenhanced CT. In addition to detection of active bleeding, an advantage of contrast-enhanced MDCT is the ability to demonstrate morphologic changes in the GI tract, which could suggest specific conditions that cause acute GI bleeding such as intestinal tumors. Arterial phase contrast-enhanced MDCT is rapid, noninvasive, and accurate in detecting and localizing sites of bleeding in patients with acute GI bleeding. Contrast-enhanced MDCT may be a promising diagnostic option in patients with acute GI bleeding.

Automatic segmentation of the liver in CT images using the watershed algorithm based on morphological filtering

Liver segmentation is one of the most basic and important parts in computer-aided diagnosis for liver CT. Although various segmentation methods have been proposed for medical imaging, most of them generally do not perform well in segmenting the liver from CT images because of surface features of the liver and difficulty of discrimination from other adjacent organs. In this paper, we propose a new scheme for automatic segmentation of the liver in CT images. The pro-posed scheme is carried out on region-of-interest (ROI) blocks that include regions of the liver with high probabilities. The ROI approach saves unnecessary computational loss in finding the accurate boundary of the liver. The proposed method utilizes the composition of morphological filters with a priori knowledge, such as the general location or the approximate intensity of the liver to detect the initial boundary of the liver. Then, we make the gradient image with the weight of an initial liver boundary and segment the liver region by using an immersion-based watershed algorithm in the gradient image. Finally, a refining process is carried out to acquire a more accurate liver region.

Segmentation of the liver using the deformable contour method on CT images

Automatic liver segmentation from abdominal computed tomography (CT) images is one of the most important steps for computer-aided diagnosis (CAD) for liver CT. However, the liver must be separated manually or semi-automatically since surface features of the liver and partial-volume effects make automatic discrimination from other adjacent organs or tissues very difficult. In this paper, we present an unsupervised liver segmentation algorithm with three steps. In the preprocessing, we simplify the input CT image by estimating the liver position using a prior knowledge about the location of the liver and by performing multilevel threshold on the estimated liver position. The proposed scheme utilizes the multiscale morphological filter recursively with region-labeling and clustering to detect the search range for deformable contouring. Most of the liver contours are positioned within the search range. In order to perform an accurate segmentation, we produce the gradient-label map, which represents the gradient magnitude in the search range. The proposed algorithm performed deformable contouring on the gradient-label map by using regular patterns of the liver boundary. Experimental results are comparable to those of manual tracing by radiological doctors and shown to be efficient.

Prognostic value of preoperative radiological staging assessed by computed tomography in patients with nonmetastatic colon cancer

PURPOSE This study evaluated the prognostic value of preoperative locoregional staging in patients with colon cancer and who underwent curative resection. METHODS A total of 536 consecutive patients who underwent curative resection for colon cancer from February 1999 to November 2007 were prospectively enrolled. The clinicopathological variables, including the radiological staging using computed tomography, were analyzed for the prognostic significance. RESULTS The 5-year overall survival rates of the patients with radiological T1, T2, T3, and T4 were 96%, 89%, 75%, and 79%, respectively (P = 0.028). The 5-year overall survival rates were 83%, 76%, and 54%, respectively, for patients with radiological N0, N1, and N2 disease (P < 0.001). The 5-year overall survival rates of the patients with radiological TNM (tumor-node-metastasis) stages I, II, and III were 90%, 81%, and 70%, respectively (P < 0.001) and the 5-year overall survival rates of the patients with pathological TNM stages I, II, and III were 93%, 80%, and 70%, respectively (P = 0.001). On multivariate analysis, the radiological T and N categories remained independent prognostic factors for both overall survival and disease-free survival. CONCLUSION Radiological staging is an independent predictor of long-term survival in the preoperative setting.PURPOSE This study evaluated the prognostic value of preoperative locoregional staging in patients with colon cancer and who underwent curative resection. METHODS A total of 536 consecutive patients who underwent curative resection for colon cancer from February 1999 to November 2007 were prospectively enrolled. The clinicopathological variables, including the radiological staging using computed tomography, were analyzed for the prognostic significance. RESULTS The 5-year overall survival rates of the patients with radiological T1, T2, T3, and T4 were 96%, 89%, 75%, and 79%, respectively (P = 0.028). The 5-year overall survival rates were 83%, 76%, and 54%, respectively, for patients with radiological N0, N1, and N2 disease (P < 0.001). The 5-year overall survival rates of the patients with radiological TNM (tumor-node-metastasis) stages I, II, and III were 90%, 81%, and 70%, respectively (P < 0.001) and the 5-year overall survival rates of the patients with pathological TNM stages I, II, and III were 93%, 80%, and 70%, respectively (P = 0.001). On multivariate analysis, the radiological T and N categories remained independent prognostic factors for both overall survival and disease-free survival. CONCLUSION Radiological staging is an independent predictor of long-term survival in the preoperative setting.

Noninvasive biomarkers for acute hepatotoxicity induced by 1,3-dichloro-2-propanol: hyperpolarized 13C dynamic MR spectroscopy

The purpose of this study was to investigate the cellular metabolite change for acute hepatotoxicity induced by 1,3-dichloro-2-propanol (1,3-DCP) in rats and its correlations with the enzyme levels. In order to induce acute hepatotoxicity, a single subcutaneous injection of 1,3-DCP (80 mg/kg) was given to six male Sprague-Dawley rats. Hyperpolarized (13)C dynamic magnetic resonance spectroscopy (MRS) was performed on rat liver following injection of hyperpolarized [1-(13)C] pyruvate. The levels of serum aspartate am inotransferase (AST), alanine aminotransferase (ALT), and lactate dehydrogenase (LDH) in the 1,3-DCP treated rats were significantly increased as compared with those in normal rats. In the dynamic (13)C MR spectra, the ratios of [1-(13)C] lactate to the total carbon and [1-(13)C] alanine to the total carbon in the 1,3-DCP treated rats were significantly increased, and there were positive correlations between cellular metabolic changes and enzyme levels. The levels of [1-(13)C] lactate and [1-(13)C] alanine are potentially considered as important biomarkers for the 1,3-DCP-induced acute hepatotoxicity.

Transcatheter Coil Embolization of an Arc of Buhler Aneurysm

We report the findings of a patient with an asymptomatic Arc of Buhler (AOB) aneurysm, which was successfully treated by transcatheter coil embolization. An abdominal CT and angiography revealed an intact pancreaticoduodenal artery arcade (PDAA) and an anomalous communication between the SMA and celiac axis, termed an AOB. An aneurysm was observed at the origin of the AOB and treated with a transcatheter embolization using coils. A follow-up CT imaging confirmed the total occlusion of the aneurysm with a patent PDAA. The successful results of this treatment suggest that the endovascular therapy of an AOB aneurysm with a celiac axis occlusion and an intact PDAA is feasible and safe.

A new general method of 3D model generation for active shape image segmentation

For 3D model-based approaches, building the 3D shape model from a training set of segmented instances of an object is a major challenge and currently remains an open problem. In this paper, we propose a novel, general method for the generation of 3D statistical shape models. Given a set of training 3D shapes, 3D model generation is achieved by 1) building the mean model from the distance transform of the training shapes, 2) utilizing a tetrahedron method for automatically selecting landmarks on the mean model, and 3) subsequently propagating these landmarks to each training shape via a distance labeling method. Previous 3D modeling efforts all had severe limitations in terms of the object shape, geometry, and topology. The proposed method is very general without such assumptions and is applicable to any data set.

MR Imaging of Brain: Comparison between SS-FSE and Fast Spin-Echo T2-Weighted Pulse Sequences

We compared quantitatively and qualitatively a single shot fast spin-echo (SS-FSE) technique with a T2-weighted fast spin-echo (T2-FSE) technique and to determine whether SS-FSE is a valuable alternative to fast SE (FSE) imaging. A total of 41 consecutive patients with brain lesions were retrospectively evaluated. Together with quantitative analysis, contrast-to-noise ratios (CNR), signal-to-noise ratios (SNR), and the percent contrast (%C) were measured for the lesion. Images were evaluated by two radiologists who reached consensus. Visibility (detection), margination, and extent of the lesions were rated separately, according to a five-point scale. The mean lesion CNR was significantly higher on SS-FSE sequences than on fast SE sequences (p=0.0131). The mean lesion %C was also higher on SS-FSE than on T2-FSE sequence (p=0.0222). However, the mean lesion SNR was significantly higher on T2-FSE sequence than on SSFSE sequence (p?0.0222). No significant differences were found in the visibility (detectability) of the lesions between two pulse sequences (p=0.1323). The SS-FSE technique is quantitatively superior to T2-FSE for obtaining T2-weighted images of the brain. In comparison with T2-FSE, SS-FSE provides comparable T2-weighted images with sufficient contrast in the evaluation of brain lesions. Our findings suggest that SSFSE may be useful for ill, uncooperative patients, especially for the children patients requiring sedation.