Tuning kernel function parameters of support vector machines for segmentation of lung disease patterns in high-resolution computed tomography images

The analysis and interpretation of high-resolution computed tomography (HRCT) images of the chest in the presence of interstitial lung disease (ILD) is a time-consuming task which requires experience. In this paper, a computer-aided diagnosis (CAD) scheme is proposed to assist radiologists in the differentiation of lung patterns associated with ILD and healthy lung parenchyma. Regions of interest were described by a set of texture attributes extracted using differential lacunarity (DLac) and classical methods of statistical texture analysis. The proposed strategy to compute DLac allowed a multiscale texture analysis, while maintaining sensitivity to small details. Support Vector Machines were employed to distinguish between lung patterns. Training and model selection were performed over a stratified 10-fold cross-validation (CV). Dimensional reduction was made based on stepwise regression (F-test,pvalue < 0.01) during CV. An accuracy of 95.8 ± 2.2% in the differentiation of normal lung pattern from ILD patterns and an overall accuracy of 94.5 ± 2.1% in a multiclass scenario revealed the potential of the proposed CAD in clinical practice. Experimental results showed that the performance of the CAD was improved by combining multiscale DLac with classical statistical texture analysis.

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Unbalanced data classification using support vector machines with active learning on scleroderma lung disease patterns

Journal of Applied Statistics ◽

10.1080/02664763.2014.978270 ◽

2014 ◽

Vol 42 (3) ◽

pp. 676-689 ◽

Cited By ~ 9

Author(s):

J. Lee ◽

Y. Wu ◽

H. Kim

Keyword(s):

Support Vector Machines ◽

Active Learning ◽

Lung Disease ◽

Data Classification ◽

Support Vector ◽

Unbalanced Data ◽

Disease Patterns ◽

Vector Machines

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Computer-Aided Quantification of Interstitial Lung Disease from High Resolution Computed Tomography Images in Systemic Sclerosis: Correlation with Visual Reader-Based Score and Physiologic Tests

BioMed Research International ◽

10.1155/2015/834262 ◽

2015 ◽

Vol 2015 ◽

pp. 1-8 ◽

Cited By ~ 13

Author(s):

Fausto Salaffi ◽

Marina Carotti ◽

Silvia Bosello ◽

Alessandro Ciapetti ◽

Marwin Gutierrez ◽

...

Keyword(s):

Computed Tomography ◽

Systemic Sclerosis ◽

High Resolution ◽

Interstitial Lung Disease ◽

Lung Disease ◽

Pulmonary Function Tests ◽

Linear Regression Analysis ◽

Receiver Operating Curve ◽

High Resolution Computed Tomography ◽

Computed Tomography Images

Objective.To evaluate the performance of a computerized-aided method (CaM) for quantification of interstitial lung disease (ILD) in patients with systemic sclerosis and to determine its correlation with the conventional visual reader-based score (CoVR) and the pulmonary function tests (PFTs).Methods.Seventy-nine patients were enrolled. All patients underwent chest high resolution computed tomography (HRCT) scored by two radiologists adopting the CoVR. All HRCT images were then analysed by a CaM using a DICOM software. The relationships among the lung segmentation analysis, the readers, and the PFTs results were calculated using linear regression analysis and Pearson’s correlation. Receiver operating curve analysis was performed for determination of CaM extent threshold.Results.A strong correlation between CaM and CoVR was observed (P<0.0001). The CaM showed a significant negative correlation with forced vital capacity (FVC) (P<0.0001) and the single breath carbon monoxide diffusing capacity of the lung (DLco) (P<0.0001). A CaM optimal extent threshold of 20% represented the best compromise between sensitivity (75.6%) and specificity (97.4%).Conclusions.CaM quantification of SSc-ILD can be useful in the assessment of extent of lung disease and may provide reliable tool in daily clinical practice and clinical trials.

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AB0605 CLINICAL PROFILE AND CHEST HIGH-RESOLUTION COMPUTED TOMOGRAPHY (HRCT) FINDINGS IN PATIENTS WITH CONNECTIVE TISSUE DISEASES AND INTERSTITIAL LUNG DISEASE: EXPERIENCE OF A SINGLE REFERENCE RHEUMATOLOGY CENTER

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2020-eular.3758 ◽

2020 ◽

Vol 79 (Suppl 1) ◽

pp. 1598.2-1599

Author(s):

I. Rusu ◽

L. Muntean ◽

M. M. Tamas ◽

I. Felea ◽

L. Damian ◽

...

Keyword(s):

Computed Tomography ◽

Systemic Sclerosis ◽

High Resolution ◽

Interstitial Lung Disease ◽

Connective Tissue ◽

Lung Disease ◽

Interstitial Pneumonia ◽

Connective Tissue Diseases ◽

High Resolution Computed Tomography ◽

Hrct Patterns

Background:Interstitial lung disease (ILD) is a common manifestation of connective tissue diseases (CTDs), and is associated with significant morbidity and mortality. Chest high-resolution computed tomography (HRCT) play an important role in the diagnosis of ILD and may provide prognostic information.Objectives:We aimed to characterize the clinical profile and chest HRCT abnormalities and patterns of patients diagnosed with CTDs and ILD.Methods:In this retrospective, observational study we included 80 consecutive patients with CTDs and ILD referred to a tertiary rheumatology center between 2015 and 2019. From hospital charts we collected clinical data, immunologic profile, chest HRCT findings. HRCT patterns were defined according to new international recommendations.Results:Out of 80 patients, 64 (80%) were women, with a mean age of 55 years old. The most common CTD associated with ILD was systemic sclerosis (38.8%), followed by polymyositis (22.5%) and rheumatoid arthritis (18.8%). The majority of patients had dyspnea on exertion (71.3%), bibasilar inspiratory crackles were present in 56.3% patients and 10% had clubbing fingers. Antinuclear antibodies (ANA) were present in 78.8% patients, and the most frequently detected autoantibodies against extractable nuclear antigen were anti-Scl 70 (28.8%), followed by anti-SSA (anti-Ro, 17.5%), anti-Ro52 (11.3%) and anti-Jo (7.5%). Intravenous cyclophosphamide therapy for 6-12 months was used in 35% of patients, while 5% of patients were treated with mycophenolate mofetil.The most frequent HRCT abnormalities were reticular abnormalities and ground glass opacity. Non-specific interstitial pneumonia (NSIP) was identified in 46.3% CTDs patients. A pattern suggestive of usual interstitial pneumonia (UIP) was present in 32.5% patients, mainly in patients with systemic sclerosis. In 21.3% patients the HRCT showed reticulo-nodular pattern, micronodules and other abnormalities, not diagnostic for UIP or NSIP pattern.Conclusion:Nonspecific interstitial pneumonia (NSIP) is the most common HRCT pattern associated with CTDs. Further prospective longitudinal studies are needed in order to determine the clinical and prognostic significance of various HRCT patterns encountered in CTD-associated ILD and for better patient management.References:[1]Ohno Y, Koyama H, Yoshikaua T, Seki S. State-of-the-Art Imaging of the Lung for Connective Tissue Disease (CTD). Curr Rheumatol Rep. 2015;17(12):69.[2]Walsh SLF, Devaraj A, Enghelmeyer JI, Kishi K, Silva RS, Patel N, et al. Role of imaging in progressive-fibrosing interstitial lung diseases. Eur Respir Rev. 2018;27(150)Disclosure of Interests:None declared

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