Semiautomatic Evaluation Procedures for Quantitative CT of the Lung

Kalender, Willi A.; Fichte, Heinz; Bautz, W.; Skalej, Martin

doi:10.1097/00004728-199103000-00011

Cited by 146 publications

(67 citation statements)

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“…Subse quently, the uniformity of the data is much higher than in studies using manual segmen tation of structures or organs [5,9,14]. In an analogy to the deviations of lung density measurements occurring at manual segmen tation of the lung, a similar bias can be ex pected for volume calculations based on manual segmentations [4]. Simple multipli cation of organ area and slice thickness is generally accepted for calculations of organ volumes[5, 9,10,14].…”

Section: Discussionmentioning

confidence: 99%

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Assessment of lung volumes using helical CT at inspiration and expiration: comparison with pulmonary function tests.

Kauczor¹,

Heußel²,

Fischer³

et al. 1998

American Journal of Roentgenology

142

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This study was designed to determine lung volumes using inspiratory and expiratoryhelicalCT with two-dimensional (2D) andthree-dimensional (3D) postprocessing and to compare the accuracy of those measurementswith pulmonary function test results. SUBJECTS AND METHODS.Seventy-two patients with suspected pulmonary disease underwent unenhanced helical CT (slice thickness, 8 mm; pitch, 2; increment, 8 mm) at deep inspiration and expiration. Lung volumes were determined using either a 2D approach (semi automatic segmentation; thresholds, â€"¿ 1024 and â€"¿ 200 H) or a 3D technique (double-threshold seeded volumes of interest; thresholds, â€"¿ 1024 H [lower] and â€"¿ 900, â€"¿ 500, â€"¿ 400, â€"¿ 300, or â€"¿ 200 H [upper]). Pulmonary function tests were available for correlation in all cases.RESULTS. Using inspiratory helical CT, we underestimated total lung capacity by 12%, which had a goodcorrelation( r = .89) with staticlung volumes.Volumerevealedby expira tory helical CT was equivalent to intrathoracic gas volume, which also exhibited a good corre lation ( r = .88). However, using expiratory helical CT, we overestimated residual volume by ml with a rather good correlation ( r = .77). An emphysema index revealed moderate correlation with the relative forced expiratory volume in I sec (inspiration, r = â€"¿ .66; expiration, r = â€"¿ .54), whereas the expired volume showed a moderate correlation with the absolute forced expiratory volume in I sec ( r = .65). The 2D approach showed lower absolute volumes than the 3D technique (mean, 3.6%; r = .99). In the 3D technique, lower upper thresholds led to reduced volumes (170 ml/l00 H). CONCLUSION.Inspiratory and expiratory helical CT show high correlation with static lung volumes. The 3D technique (â€"1024 to â€"¿ 200 H) is recommendedfor absoluteestimation of lung volumes.L ung volumes are routinely as sessedusing pulmonary function tests.Thesetestsallow global mea surement of static inspiratoty volumes (total lung capacity); static expiratory volumes (in trathoracic gasvolumeafternormalexpiration and the residual volume after maximum expi ration); and dynamic volumes, like the abso lute and relative forced expiratory volume in 1 sec (FEV1). However, measurement of unilat eral or regional lung volumes is a major chal lenge in lung function testing.Helical CT is widely regarded as the im aging technique of choice for the radiologic assessment of the thorax [ I , 2]. A volume ac quisition of the lungs can be obtained in a single breath-hold of about 20 sec. Global, regional, and density-based (emphysema in dex) area and volume measurementscan be easily performed. The purpose of our study was to evaluate the accuracy with respect to pulmonary function tests of measurements of lung volumes and hyperinflation based on helical CT scans obtained at inspiration and expiration. Different postprocessing tech niques and different thresholds, including the emphysema index, were compared. Subjects and Methods PatientsSeventy-twopatients(58 men, 14women)with a median age of 59 years (ra...

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Section: Discussionmentioning

confidence: 99%

“…Besides the widely used upper thresholdofâ€"200 H [4], â€"¿ 500 H had beenrec Helical CT for Assessment of Lung Volumes ommended [5' 2 11. Using this threshold, the prediction of postoperative lung volumes yielded best results [5].…”

Section: Discussionmentioning

confidence: 99%

Assessment of lung volumes using helical CT at inspiration and expiration: comparison with pulmonary function tests.

Kauczor¹,

Heußel²,

Fischer³

et al. 1998

American Journal of Roentgenology

142

View full text Add to dashboard Cite

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“…By this means, images were rendered legible for the image analysis software package Optimas TM , version 4.1 (Bioscan Inc., Edmonds, WA, USA). For each scan, the left and right lung contours were traced by a semi-automatic technique [6]. To mask lung tissue densities, automatic tracing by an algorithm based on the standard formula for polygonal areas was performed.…”

Section: Atelectasismentioning

confidence: 99%

Position and shape of the diaphragm: implications for atelectasis formation

1998

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SummaryTo evaluate diaphragm movement, 18 consecutive patients undergoing surgery under general anaesthesia were allocated to Group 1 (n ¼ 9: no neuromuscular paralysis) or Group 2 (n ¼ 9: neuromuscular paralysis achieved with pancuronium). Spiral computerised tomography was performed awake and during anaesthesia at end-expiratory level and, additionally, in four patients (Group 2) at end-inspiration for subsequent analysis. There was a significant cephalad displacement of the most cephalad point of the diaphragm dome at functional residual capacity, particularly in its dependent portion, in the pancuronium group. During anaesthesia with no persisting muscle paralysis, there was only a minor and insignificant cephalad shift of the diaphragm dome. However, regional analysis showed that the most dorsal part of the diaphragm was significantly displaced cephalad. Compared with conscious, spontaneous breathing, mechanical ventilation decreased the inspiratory displacement of the dependent part of the muscle. This minor movement of the diaphragm may play an additional role in atelectasis formation.

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“…However, most of the existing methods have used thresholding [1, 2, 9 10 and 11] based methods for segmentation. Moreover, there are many methods like Watershed Transform [3,7], Region growing algorithm [4], Model-based methods, edge-tracking approach [17], 3D modelling [22], and Multiscale morphological segmentation techniques [18,5].…”

Section: Introductionmentioning

confidence: 99%

Intelligent Segmentation of Medical Images Using Fuzzy Bitplane Thresholding

Khan

Kannan

2014

Measurement Science Review

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The performance of assessment in medical image segmentation is highly correlated with the extraction of anatomic structures from them, and the major task is how to separate the regions of interests from the background and soft tissues successfully. This paper proposes a fuzzy logic based bitplane method to automatically segment the background of images and to locate the region of interest of medical images. This segmentation algorithm consists of three steps, namely identification, rule firing, and inference. In the first step, we begin by identifying the bitplanes that represent the lungs clearly. For this purpose, the intensity value of a pixel is separated into bitplanes. In the second step, the triple signum function assigns an optimum threshold based on the grayscale values for the anatomical structure present in the medical images. Fuzzy rules are formed based on the available bitplanes to form the membership table and are stored in a knowledge base. Finally, rules are fired to assign final segmentation values through the inference process. The proposed new metrics are used to measure the accuracy of the segmentation method. From the analysis, it is observed that the proposed metrics are more suitable for the estimation of segmentation accuracy. The results obtained from this work show that the proposed method performs segmentation effectively for the different classes of medical images.

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Semiautomatic Evaluation Procedures for Quantitative CT of the Lung

Cited by 146 publications

References 0 publications

Assessment of lung volumes using helical CT at inspiration and expiration: comparison with pulmonary function tests.

Assessment of lung volumes using helical CT at inspiration and expiration: comparison with pulmonary function tests.

Position and shape of the diaphragm: implications for atelectasis formation

Intelligent Segmentation of Medical Images Using Fuzzy Bitplane Thresholding

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