• Korean Journal of Radiology
• /
• 제1권2호
• /
• pp.110-113
• /
• 2000

Objective: The purpose of this study was to determine, when measuring prostate volume by TRUS, whether height is more accurately determined by transaxial or midsagittal scanning. Materials and Methods: Sixteen patients who between March 1995 and March 1998 underwent both preoperative TRUS and radical prostatectomy for prostate cancer were included in this study. Using prolate ellipse volume calculation (height × length × width × 𝜋/6), TRUS prostate volume was determined, and was compared with the measured volume of the specimen. Results: Prostate volume measured by TRUS, regardless of whether height was determined transaxially or midsagittally, correlated closely with real specimen volume. When height was measured in one of these planes, a paired t test revealed no significant difference between TRUS prostate volume and real specimen volume (p = .411 and p = .740, respectively), nor were there significant differences between the findings of transaxial and midsagittal scanning (p = .570). A paired sample test, however, indicated that TRUS prostate volumes determined transaxially showed a higher correlation coefficient (0.833) and a lower standard deviation (9.04) than those determined midsagittally (0.714 and 11.48, respectively). Conclusion: Prostate volume measured by TRUS closely correlates with real prostate volume. Furthermore, we suggest that when measuring prostate volume in this way, height is more accurately determined by transaxial than by midsagittal scanning.

• 한국컴퓨터정보학회논문지
• /
• 제17권12호
• /
• pp.101-109
• /
• 2012

TRUS영상에서 전립선에 대한 많은 진단과 치료 과정에서 정확한 전립선 경계의 추출이 요구된다. 여기에는 전립선 경계의 애매함, 반점, 낮은 그레이 레벨로 인하여 많은 어려움이 존재한다. 본 논문에서는 서포트 벡터와 뱀형상 윤곽선을 이용하여 TRUS영상의 자동 전립선 분할에 대한 방법을 제안한다. 이 방법은 전처리, 가버 특성 추출, 학습, 전립선 추출 단계로 구성된다. 텍스처 특성을 추출하기 위하여 가버 필터 뱅크가 사용되며, 학습 과정에서 전립선과 비전립선의 각 특성을 얻기 위하여, SVM이 사용된다. 전립선의 경계는 뱀형상 윤곽 알고리즘에 의해 추출된다. 실험 결과, 제안된 알고리즘은 인간 전문가가 추출한 경계와 비교했을 때 9.3%보다 적은 차이로 전립선 경계를 추출할 수 있었다.

• 디지털콘텐츠학회 논문지
• /
• 제15권6호
• /
• pp.675-682
• /
• 2014

전립선은 남자에게만 있는 장기이다. 전립선의 질병을 진단하기 위하여 일반적으로 TRUS 영상이 사용되는데, 희미한 전립선 경계나 잡음, 좁은 그레이 레벨 분포 때문에, 전립선의 경계를 검출하는 것은 상당히 어려운 작업 중의 하나이다. 본 논문에서는 SVM을 사용하여 TRUS 영상에서 자동적으로 전립선 분할을 하는 방법을 제안한다. 이 방법은 전처리, 가버 특징 추출, 훈련, 전립선 분할 과정으로 진행된다. 전처리 과정에서 잡음 제거는 스틱 필터와 top-hat 변환이 적용된다. 회전 불변 텍스처 추출을 위하여 가버 필터 뱅크가 사용된다. 훈련과정에서 SVM은 전립선과 비전립선의 각 특징을 얻기 위해 사용되며, 마지막으로 전립선 경계가 추출된다. 여러 실험 결과로 제안 방법은 충분히 유효하고, 의사의 수동 추출 방법과 비교했을 때 10%미만의 경계 차이를 보였다.

• Journal of Yeungnam Medical Science
• /
• 제21권2호
• /
• pp.191-197
• /
• 2004

Background: This study was performed to reconsider the efficacy of transrectal ultrasonography (TRUS) in diagnosing prostate cancer by analyzing the results of a digital rectal examination (DRE), serum prostate-specific antigen (PSA) and a transrectal ultrasonography in patients with prostate specific antigen levels of 10 ng/ml or less. Materials and Methods: One-hundred and eighty one men with PSA levels of 10 ng/ml or less, who had a TRUS-guided tissue biopsy performed, were included in this study. The detection rate of prostate cancer was compared according to the TRUS result and the presence or absence of nodularity and the consistency of the prostate on DRE. Results: In a total 181 patients, there were 73 patients with PSA levels of 4 ng/ml or less and 4 of them had prostate cancer. Thre were 108 patients with PSA levels of 4-10 ng/ml and 18 of them were prostate cancer. TRUS was performed in 152 patients and 16 out of 58 patients diagnosed with prostate cancer, 3 out of 39 diagnosed with suspicious prostate cancer, and 2 out of 55 patients diagnosed as having no prostate cancer were found to have prostate cancer. In 40 patients, a nodule was palpated on DRE and 8 of them were found to have prostate cancer. Five out of 19 patients with a stony hard consistency, 3 of 12 with a firm to hard consisency, 12 of 129 with a firm consistency, 0 of 13 with a soft to firm consistency, and 2 of 8 with a soft consistency were prostate cancer. In the prostate cancer patients, there were 4 patients with PSA levels of 4 ng/ml or less and all these patients were diagnosed with prostate cancer or suspicious prostate cancer on TRUS but the nodule was not palpated in all patients. Two were soft and 2 were firm consistency on DRE. Conclusion: In patients with serum PSA levels of 10 ng/ml or less, TRUS is a more useful supporting method than DRE and a more active application of TRUS may lead to an early diagnosis and pertinent treatment of prostate cancer.

• Korean Journal of Radiology
• /
• 제2권3호
• /
• pp.159-163
• /
• 2001

Objective: The purpose of this study is to correlate the findings of peripheral hypoechoic rim, seen at transrectal ultrasonography (TRUS) in chronic prostatitis patients, with the histopthologic findings. Materials and Methods: Seven patients with pathologically proven chronic prostatitis were involved in this study. The conspicuity of the peripheral hypoechoic prostatic rim, seen at TRUS, was prominent and subtle, and to determine its histopathologic nature, the microscopic findings were reviewed. Results: In five of seven cases (71%), TRUS demonstrated a prominent peripheral hypoechoic rim. Microscopic examination revealed that inflammatory cell infiltration of prostatic glandular tissue was severe in three cases (42.9%), moderate in two (28.6%), and minimal in two (28.6%). In all seven cases, the common histopathologic findings of peripheral hypoechoic rim on TRUS were loose stromal tissues, few prostatic glands, and sparse infiltration by inflammatory cells. Conclusion: The peripheral hypoechoic rim accompanying prostatic inflammation and revealed by TRUS reflects a sparsity of prostate glandular tissue and is thought to be an area in which inflammatory cell infiltration is minimal.

• 정보처리학회논문지:소프트웨어 및 데이터공학
• /
• 제3권5호
• /
• pp.187-194
• /
• 2014

전립선암은 전립선에 나타나는 악성 종양이다. 현재 그 발병률이 높아지고 있다. 전립선암의 구조를 가장 정확하게 확인할 수 있는 검사 방법은 MRI를 이용하는 것이나, 그 비용 때문에 모든 환자에게 적용하기는 어려운 실정이다. 그래서 많은 환자들은 가격이 저렴한 초음파검사를 이용하여 전립선암을 진단하고 있다. 전통적으로 의사들은 영상을 눈으로 확인하여 전립선의 경계를 수동으로 분할하였다. 그러나 수동으로 분할하는 과정은 시간이 많이 소요되며, 의사에 따라서 그 경계가 일정하지 않게 얻어진다. 이 문제를 해결하기 위하여 전립선의 자동 분할에 관한 연구가 되었고, 환자들에게 신뢰를 줄 수 있었다. 본 연구는 초음파 전립선 영상에서 전립선의 경계를 분할하는데 평균 형상 모델을 적용하는 것이다. 먼저, 에지 분포를 이용하여 프로브를 찾고, 프로브와 연결된 두 직선을 찾는다. 이 후에 이 정보를 이용하여 전립선 영상 위에 평균 형상을 위치시킨다.

• Asian Pacific Journal of Cancer Prevention
• /
• 제15권7호
• /
• pp.3087-3091
• /
• 2014

Purpose: To determine the utility of digital rectal examination (DRE), serum total prostate specific antigen (tPSA) estimation, and transrectal ultrasound (TRUS) for the detection of prostate cancer (PCa) in men with lower urinary tract symptoms (LUTS). Materials and Methods: All patients with abnormal DRE, TRUS, or serum tPSA >4ng/ml, in any combination, underwent TRUS-guided needle biopsy. Eight cores of prostatic tissue were obtained from different areas of the peripheral prostate and examined histopathologically for the nature of the pathology. Results: PCa was detected in 151 (50.3%) patients, remaining 149 (49.7%) showed benign changes with or without active prostatitis. PCa was detected in 13 (56.5%), 9 (19.1%), 26 (28.3%), and 103 (74.6%) of patients with tPSA <4 ng/ml, 4-10 ng/ml, 10-20 ng/ml and >20 ng/ml respectively. Only 13 patients with PCa had abnormal DRE and TRUS with serum PSA <4 ng/ml. The detection rate was highest in patients with tPSA >20 ng/ml. The association between tPSA level and cancer detection was statistically significant (p<0.01). Among 209 patients with abnormal DRE and raised serum PSA, PCa was detected in 128 (61.2%). Conclusions: The incidence of PCa increases with increasing serum level of tPSA. The overall screening and detection rate can be further improved by using DRE, TRUS and TRUS-guided prostate needle biopsies.

• 정보처리학회논문지:소프트웨어 및 데이터공학
• /
• 제1권3호
• /
• pp.187-194
• /
• 2012

전립선암은 남자에게 가장 흔히 나타나는 암 중의 하나이며, 많은 나라에서 죽음에 이르게 하는 큰 요인이 되고 있다. 전립선암을 진단하고 치료하는 과정에서 비용이 싼 TRUS 영상이 사용된다. 그러나 전립선 경계의 정확한 구분이 요구되지만 어려운 문제이다. 그 이유는 경계가 불명확하고, 반점들이 많으며, 그레이 레벨의 범위가 작기 때문이다. 본 연구에서는 전립선의 평균 형상 모델과 불변의 특징을 이용하여 TRUS 영상에서 자동으로 전립선 분할하는 방법을 제안한다. 이 방법은 4 단계로 구성된다. 먼저, 에지 분포를 이용하여 프로브와 두개의 직선을 찾아낸다. 다음으로, 평균 형상 모델의 중앙에 위치한 3개의 전립선 패치를 획득한다. 이 패치는 전립선과 비전립선의 특징을 비교하기 위해 사용된다. 다음으로, 세 개의 패치와 각 블록들이 얼마나 대표 블록과 유사한지를 비교한다. 마지막으로, 앞 단계의 경계와 첫 단계에서 얻은 개략적 경계가 최종 분할에 사용된다. 이 방법의 유효성을 검증하기 위하여 실험을 하였으며, 인간 전문가에 의해 얻어진 경계와 비교하여 7.78% 미만의 차이로 경계를 얻을 수 있었다.

• Journal of Computational Design and Engineering
• /
• 제1권4호
• /
• pp.272-288
• /
• 2014

This paper presents a two-step, semi-automated method for reconstructing a three-dimensional (3D) shape of the prostate from a 3D transrectal ultrasound (TRUS) image. While the method has been developed for prostate ultrasound imaging, it can potentially be applicable to any other organ of the body and other imaging modalities. The proposed method takes as input a 3D TRUS image and generates a watertight 3D surface model of the prostate. In the first step, the system lets the user visualize and navigate through the input volumetric image by displaying cross sectional views oriented in arbitrary directions. The user then draws partial/full contours on selected cross sectional views. In the second step, the method automatically generates a watertight 3D surface of the prostate by fitting a deformable spherical template to the set of user-specified contours. Since the method allows the user to select the best cross-sectional directions and draw only clearly recognizable partial or full contours, the user can avoid time-consuming and inaccurate guesswork on where prostate contours are located. By avoiding the usage of noisy, incomprehensible portions of the TRUS image, the proposed method yields more accurate prostate shapes than conventional methods that demand complete cross-sectional contours selected manually, or automatically using an image processing tool. Our experiments confirmed that a 3D watertight surface of the prostate can be generated within five minutes even from a volumetric image with a high level of speckles and shadow noises.

• Journal of Information Processing Systems
• /
• 제9권1호
• /
• pp.103-116
• /
• 2013

Prostate cancer is one of the most frequent cancers in men and is a major cause of mortality in the most of countries. In many diagnostic and treatment procedures for prostate disease accurate detection of prostate boundaries in transrectal ultrasound(TRUS) images is required. This is a challenging and difficult task due to weak prostate boundaries, speckle noise and the short range of gray levels. In this paper a method for automatic prostate segmentation in TRUS images using Gabor feature extraction and snake-like contour is presented. This method involves preprocessing, extracting Gabor feature, training, and prostate segmentation. The speckle reduction for preprocessing step has been achieved by using stick filter and top-hat transform has been implemented for smoothing the contour. A Gabor filter bank for extraction of rotation-invariant texture features has been implemented. A support vector machine(SVM) for training step has been used to get each feature of prostate and nonprostate. Finally, the boundary of prostate is extracted by the snake-like contour algorithm. A number of experiments are conducted to validate this method and results showed that this new algorithm extracted the prostate boundary with less than 10.2% of the accuracy which is relative to boundary provided manually by experts.