Unlabelled: Our objective was to develop and evaluate 3 semiautomatic computer-aided diagnostic (CAD) schemes for distinguishing between benign and malignant pulmonary nodules by use of features extracted from CT, 18F-FDG PET, and both CT and 18F-FDG PET.
Methods: We retrospectively collected 92 consecutive cases of pulmonary nodules (<3 cm) in patients who underwent both thoracic CT and whole-body PET/CT. Forty-two of the nodules were malignant and 50 benign, as confirmed by pathologic examination and clinical follow-up. The interval between CT and PET was less than 1 mo. Four clinical parameters, including patient age, sex, smoking status, and history of previous malignancy, were used for the CAD schemes. Sixteen CT features based on size, shape, margin, and internal structure of nodules were independently rated subjectively by 2 chest radiologists. Four PET features were viewed on a PET/CT workstation. CAD schemes based on clinical parameters together with CT features, PET features, and both CT and PET features were then used to differentiate benign from malignant nodules. Finally, the output from the CAD schemes was evaluated by use of receiver-operating-characteristic analysis.
Results: When we used clinical parameters and CT features as input units (CAD scheme 1), the area under the receiver-operating-characteristic curve (A(z) value) of the CAD scheme was 0.83. When we used clinical parameters and PET features as input units (CAD scheme 2), the A(z) value for the computer output was 0.91. However, when we used all data as input units (CAD scheme 3), the A(z) value for the computer output was 0.95. The performance of CAD scheme 3 was better than that of CAD scheme 1 or 2. A statistically significant difference existed between the A(z) values of CAD schemes 3 and 2 (P = 0.037) and between those of CAD schemes 3 and 1 (P = 0.015).
Conclusion: Our CAD scheme based on both PET and CT was better able to differentiate benign from malignant pulmonary nodules than were the CAD schemes based on PET alone and CT alone.
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BMC Med Imaging
November 2024
Department of Industrial Engineering, Stellenbosch University, Faculty of Engineering, Banghoek Rd, Stellenbosch, Western Cape, 7600, Republic of South Africa.
Objective: To conduct a systematic review of the computer vision applications that detect, diagnose, or analyse tuberculosis (TB) pathology or bacilli using digitised human lung tissue images either through automatic or semi-automatic methods. We categorised the computer vision platform into four technologies: image processing, object/pattern recognition, computer graphics, and deep learning. In this paper, the focus is on image processing and deep learning (DL) applications for either 2D or 3D digitised human lung tissue images.
View Article and Find Full Text PDFQuant Imaging Med Surg
October 2024
International School of Information Science & Engineering (DUT-RUISE), Dalian University of Technology, Dalian, China.
Background: Accurate delineation of knee bone boundaries is crucial for computer-aided diagnosis (CAD) and effective treatment planning in knee diseases. Current methods often struggle with precise segmentation due to the knee joint's complexity, which includes intricate bone structures and overlapping soft tissues. These challenges are further complicated by variations in patient anatomy and image quality, highlighting the need for improved techniques.
View Article and Find Full Text PDFGastroenterol Rep (Oxf)
October 2024
Department of Gastrointestinal Surgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Hongkou District, Shanghai, P. R. China.
Ann Nucl Med
December 2024
Medical School, São Paulo State University Julio de Mesquita Filho, Av. Prof. Mário Rubens Guimarães Montenegro, S/N, UNESP Campus de Botucatu, Botucatu, SP, CEP: 18618687, Brazil.
Aim: CT images can identify structural and opacity alterations of the lungs while nuclear medicine's lung perfusion studies show the homogeneity (or lack of) of blood perfusion on the organ. Therefore, the use of SPECT/CT in lung perfusion scintigraphies can help physicians to assess anatomical and functional alterations of the lungs and to differentiate between acute and chronic disease.
Objective: To develop a computer-aided methodology to quantify the total global perfusion of the lungs via SPECT/CT images and to compare these results with parenchymal alterations obtained in CT images.
Heliyon
June 2024
Division of Farm Machinery & Power Engineering, Sher-e-Kashmir University of Agricultural Sciences & Technology of Jammu (SKUAST-J), Jammu, Jammu & Kashmir, India.
The process of seedling transplantation has significant importance within the realm of mechanical vegetable production in contemporary agriculture. A prototype of a two-row tractor-mounted semi-automatic vegetable seedling transplanter (SVT) was conceptualized and developed for small agricultural holdings. The functional behaviour of the prototype was examined with computer-aided design tools, and the various units of the prototype have been finalized.
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