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Nimura Y.,Nagoya University | Kitasaka T.,Aichi Institute of Technology | Honma H.,Sapporo Kosei General Hospital | Takabatake H.,Sapporo Minami sanjo Hospital | And 3 more authors.
International Journal of Computer Assisted Radiology and Surgery | Year: 2013

Purpose Chronic obstructive pulmonary disease (COPD) is characterized by airflow limitations. Physicians frequently assess the stage using pulmonary function tests and chest CT images. This paper describes a novel method to assess COPD severity by combining measurements of pulmonary function tests (PFT) and the results of chest CT image analysis. Methods The proposed method utilizes measurements from PFTs and chest CT scans to assess COPD severity. This method automatically classifies COPD severity into five stages, described in GOLD guidelines, by a multi-class AdaBoost classifier. The classifier utilizes 24 measurements as feature values, which include 18 measurements from PFTs and six measurements based on chest CT image analysis. A total of 3 normal and 46 abnormal (COPD) examinations performed in adults were evaluated using the proposed method to test its diagnostic capability. Results The experimental results revealed that its accuracy rates were 100.0 % (resubstitution scheme) and 53.1 % (leave-one-out scheme). A total of 95.7 % of missed classifications were assigned in the neighboring severities. Conclusions These results demonstrate that the proposed method is a feasible means to assess COPD severity. A much larger sample size will be required to establish the limits of the method and provide clinical validation. © 2012 CARS. Source

Chen B.,Nagoya University | Kitasaka T.,Aichi Institute of Technology | Honma H.,Sapporo Medical University | Takabatake H.,Sapporo Minami sanjo Hospital | And 3 more authors.
International Journal of Computer Assisted Radiology and Surgery | Year: 2012

Purpose Pulmonary nodules may indicate the early stage of lung cancer, and the progress of lung cancer causes associated changes in the shape and number of pulmonary blood vessels. The automatic segmentation of pulmonary nodules and blood vessels is desirable for chest computer-aided diagnosis (CAD) systems. Since pulmonary nodules and blood vessels are often attached to each other, conventional nodule detection methods usually produce many false positives (FPs) in the blood vessel regions, and blood vessel segmentation methods may incorrectly segment the nodules that are attached to the blood vessels. A method to simultaneously and separately segment the pulmonary nodules and blood vessels was developed and tested. Method A line structure enhancement (LSE) filter and a bloblike structure enhancement (BSE) filter were used to augment initial selection of vessel regions and nodule candidates, respectively. A front surface propagation (FSP) procedure was employed for precise segmentation of blood vessels and nodules. By employing a speed function that becomes fast at the initial vessel regions and slow at the nodule candidates to propagate the front surface, the front surface can be propagated to cover the blood vessel region with suppressed nodules. Hence, the resultant region covered by the front surface indicates pulmonary blood vessels. The lung nodule regions were finally obtained by removing the nodule candidates that are covered by the front surface. Result A test data set was assembled including 20 standard-dose chest CT images obtained from a local database and 20 low-dose chest CT images obtained from lung image database consortium (LIDC). The average extraction rate of the pulmonary blood vessels was about 93%. The average TP rate of nodule detection was 95% with 9.8 FPs/case in standard-dose CT image, and 91.5% with 10.5 FPs/case in low-dose CT image, respectively. Conclusion Pulmonary blood vessels and nodules segmentation method based on local intensity structure analysis and front surface propagation were developed. The method was shown to be feasible for nodule detection and vessel extraction in chest CAD. © 2011 CARS. Source

Luo X.,Nagoya University | Feuerstein M.,TU Munich | Kitasaka T.,Aichi Institute of Technology | Natori H.,Keiwakai Nishioka Hospital | And 3 more authors.
Progress in Biomedical Optics and Imaging - Proceedings of SPIE | Year: 2011

Image-guided bronchoscopy usually requires to track the bronchoscope camera position and orientation to align the preinterventional 3-D computed tomography (CT) images to the intrainterventional 2-D bronchoscopic video frames. Current state-of-the-art image-based algorithms often fail in bronchoscope tracking due to shortages of information on depth and rotation around the viewing (running) direction of the bronchoscope camera. To address these problems, this paper presents a novel bronchoscope tracking method for bronchoscopic navigation based on a low-cost optical mouse sensor, bronchial structure information, and image registration. We first utilize an optical mouse senor to automatically measure the insertion depth and the rotation of the viewing direction along the bronchoscope. We integrate the outputs of such a 2-D sensor by performing a centerline matching on the basis of bronchial structure information before optimizing the bronchoscope camera motion parameters during image registration. An assessment of our new method is implemented on phantom data. Experimental results illustrate that our proposed method is a promising means for bronchoscope tracking, compared to our previous image-based method, significantly improving the tracking performance. © 2011 SPIE. Source

Luo X.,Nagoya University | Feuerstein M.,Nagoya University | Feuerstein M.,TU Munich | Deguchi D.,Nagoya University | And 4 more authors.
Medical Image Analysis | Year: 2012

This paper presents a new hybrid camera motion tracking method for bronchoscopic navigation combining SIFT, epipolar geometry analysis, Kalman filtering, and image registration. In a thorough evaluation, we compare it to state-of-the-art tracking methods. Our hybrid algorithm for predicting bronchoscope motion uses SIFT features and epipolar constraints to obtain an estimate for inter-frame pose displacements and Kalman filtering to find an estimate for the magnitude of the motion. We then execute bronchoscope tracking by performing image registration initialized by these estimates. This procedure registers the actual bronchoscopic video and the virtual camera images generated from 3D chest CT data taken prior to bronchoscopic examination for continuous bronchoscopic navigation. A comparative assessment of our new method and the state-of-the-art methods is performed on actual patient data and phantom data. Experimental results from both datasets demonstrate a significant performance boost of navigation using our new method. Our hybrid method is a promising means for bronchoscope tracking, and outperforms other methods based solely on Kalman filtering or image features and image registration. © 2010 Elsevier B.V. Source

Kato T.,Sapporo Minami sanjo Hospital | Kato T.,Hokkaido University | Ishikawa K.,Sapporo Minami sanjo Hospital | Aragaki M.,Sapporo Minami sanjo Hospital | And 4 more authors.
Lung Cancer | Year: 2012

Angiolymphatic invasion (ALI), representing lymphatic invasion (Ly) and intratumoral vascular invasion (V), is considered to be a useful prognostic factor for pathological stage I non-small cell lung carcinoma (NSCLC). However, the types of tumor for which prognoses are most influenced by ALI positivity have not previously been discussed, nor has the question of whether these findings should influence postoperative therapeutic decision-making after complete resection. The present study investigated 195 cases of stage I NSCLC treated by potentially curative surgical resection of the primary tumor and systematic lymphadenectomy. ALI-positive (ALI(+)) results were found in 31.8% of tumors, and 5.1% exhibited both Ly(+) and V(+). Five-year recurrence-free survival was significantly lower in ALI(+) cases (50.6%) than in ALI(-) cases (85.9%; p<0.0001, log-rank test). In particular, 5-year recurrence-free survival rate was only 10.0% for Ly(+)V(+) cases. ALI(+) correlated with high age, male sex, tumor size (>2.0cm), elevated preoperative serum carcinoembryonic antigen level (≥5.0ng/mL), high maximum standard uptake value (SUVmax) on 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) (≥5.0), pleural invasion, and histological classification of non-adenocarcinoma (ADC). According to histopathological subset analyses, ALI(+) was associated with shorter recurrence-free survival than ALI(-) only among ADC patients (p<0.0001, log-rank test), and not among non-ADC patients (p=0.7710). High preoperative serum CEA level, high SUVmax on FDG-PET, pleural invasion, Ly(+), and V(+) were significant risk factors for recurrence in univariate Cox survival analysis among stage I ADC patients. Importantly, Ly(+) and V(+) were identified as independent risk factors for recurrence by multivariate analysis. Histopathological detection of ALI as a risk factor for recurrence should be considered for inclusion in the staging criteria and as additional information for determining postoperative adjuvant treatment of stage I NSCLC, particularly among ADC patients, but not among non-ADC patients. © 2012 Elsevier Ireland Ltd. Source

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