scholarly journals Mediastinal atlas creation from 3-D chest computed tomography images: Application to automated detection and station mapping of lymph nodes

2012 ◽  
Vol 16 (1) ◽  
pp. 63-74 ◽  
Author(s):  
Marco Feuerstein ◽  
Ben Glocker ◽  
Takayuki Kitasaka ◽  
Yoshihiko Nakamura ◽  
Shingo Iwano ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Lymph Nodes ◽  
Automated Detection ◽  
Chest Computed Tomography ◽  
Computed Tomography Images

Assessment of cervical lymph node metastases using indirect computed tomography lymphography with iopamidol in a tongue VX2 carcinoma model

2011 ◽  
Vol 125 (8) ◽  
pp. 820-828 ◽  
Author(s):  
Y Shu ◽  
X Xu ◽  
Z Wang ◽  
W Dai ◽  
Y Zhang ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Lymph Node ◽  
Lymph Nodes ◽  
Lymph Node Metastases ◽  
Cervical Lymph Node ◽  
Cervical Lymph Nodes ◽  
Cervical Lymph Node Metastases ◽  
Computed Tomography Images ◽  
Vx2 Carcinoma ◽  
Node Metastases

AbstractObjective:To investigate the performance of indirect computed tomography lymphography with iopamidol for detecting cervical lymph node metastases in a tongue VX2 carcinoma model.Materials and methods:A metastatic cervical lymph node model was created by implanting VX2 carcinoma suspension into the tongue submucosa of 21 rabbits. Computed tomography images were obtained 1, 3, 5, 10, 15 and 20 minutes after iopamidol injection, on days 11, 14, 21 (six rabbits each) and 28 (three rabbits) after carcinoma transplantation. Computed tomography lymphography was performed, and lymph node filling defects and enhancement characteristics evaluated.Results:Indirect computed tomography lymphography revealed bilateral enhancement of cervical lymph nodes in all animals, except for one animal imaged on day 28. There was significantly slower evacuation of contrast in metastatic than non-metastatic nodes. A total of 41 enhanced lymph nodes displayed an oval or round shape, or local filling defects. One lymph node with an oval shape was metastatic (one of 11, 9.1 per cent), while 21 nodes with filling defects were metastatic (21/30, 70 per cent). The sensitivity, specificity, accuracy, and positive and negative predictive values when using a filling defect diameter of 1.5 mm as a diagnostic criterion were 86.4, 78.9, 82.9, 82.6 and 83.3 per cent, respectively.Conclusion:When using indirect computed tomography lymphography to detect metastatic lymph nodes, filling defects and slow evacuation of contrast agent are important diagnostic features.

Ensemble U‐net‐based method for fully automated detection and segmentation of renal masses on computed tomography images

2020 ◽  
Vol 47 (9) ◽  
pp. 4032-4044 ◽  
Author(s):  
Zabihollahy Fatemeh ◽  
Schieda Nicola ◽  
Krishna Satheesh ◽  
Ukwatta Eranga
Keyword(s):  
Computed Tomography ◽  
Automated Detection ◽  
Renal Masses ◽  
Computed Tomography Images

Combined multi-kernel chest computed tomography images optimized for depicting both lung and soft tissue

2014 ◽  
Vol 38 (2) ◽  
pp. 104-108 ◽  
Author(s):  
Satoshi Takagi ◽  
Hiroyuki Nagase ◽  
Tatsuya Hayashi ◽  
Tamotsu Kita ◽  
Katsumi Hayashi ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Soft Tissue ◽  
Chest Computed Tomography ◽  
Computed Tomography Images

scholarly journals A Rare Cause of Crazy-Paving and Mediastinal Lymphadenopathy: Congestive Heart Failure

2013 ◽  
Vol 3 ◽  
pp. 30 ◽  
Author(s):  
Aysegul Senturk ◽  
Aysegul Karalezli ◽  
Ayse Nur Soyturk ◽  
H. Canan Hasanoglu
Keyword(s):  
Heart Failure ◽  
Computed Tomography ◽  
Congestive Heart Failure ◽  
Lymph Nodes ◽  
Inflammatory Diseases ◽  
Present Report ◽  
Ground Glass Opacity ◽  
Mediastinal Lymphadenopathy ◽  
Reticular Pattern ◽  
Computed Tomography Images

Crazy-paving sign is a pattern seen on multislice computed tomography images of the lungs. It is characterized by a reticular pattern superimposed on ground-glass opacity. It was first described in the late 1980s in patients with pulmonary alveolar proteinosis, but has now been described in some other diseases of the lung. Enlarged mediastinal lymph nodes can be seen in infectious and specific inflammatory diseases and malignancies. The present report describes a case of a 44-year-old man in whom congestive heart failure presented with a crazy-paving appearance and enlarged lymph nodes of the lungs on the chest computed tomography scan.

scholarly journals Rapid screening for COVID-19 by applying artificial intelligence to chest computed tomography images: A feasibility study

2021 ◽  
Vol 5 ◽  
pp. 239920262110136
Author(s):  
Pedro Galván ◽  
José Fusillo ◽  
Felipe González ◽  
Oraldo Vukujevic ◽  
Luciano Recalde ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Computed Tomography ◽  
Pleural Effusion ◽  
Feasibility Study ◽  
Ct Images ◽  
Public Hospitals ◽  
Rt Pcr ◽  
Chest Computed Tomography ◽  
Computed Tomography Images ◽  
Respiratory Conditions

Aim: The aim of the study was to present the results and impact of the application of artificial intelligence (AI) in the rapid diagnosis of COVID-19 by telemedicine in public health in Paraguay. Methods: This is a descriptive, multi-centered, observational design feasibility study based on an AI tool for the rapid detection of COVID-19 in chest computed tomography (CT) images of patients with respiratory difficulties attending the country’s public hospitals. The patients’ digital CT images were transmitted to the AI diagnostic platform, and after a few minutes, radiologists and pneumologists specialized in COVID-19 downloaded the images for evaluation, confirmation of diagnosis, and comparison with the genetic diagnosis (reverse transcription polymerase chain reaction (RT-PCR)). It was also determined the percentage of agreement between two similar AI systems applied in parallel to study the viability of using it as an alternative method of screening patients with COVID-19 through telemedicine. Results: Between March and August 2020, 911 rapid diagnostic tests were carried out on patients with respiratory disorders to rule out COVID-19 in 14 hospitals nationwide. The average age of patients was 50.7 years, 62.6% were male and 37.4% female. Most of the diagnosed respiratory conditions corresponded to the age group of 27–59 years (252 studies), the second most frequent corresponded to the group over 60 years, and the third to the group of 19–26 years. The most frequent findings of the radiologists/pneumologists were severe pneumonia, bilateral pneumonia with pleural effusion, bilateral pulmonary emphysema, diffuse ground glass opacity, hemidiaphragmatic paresis, calcified granuloma in the lower right lobe, bilateral pleural effusion, sequelae of tuberculosis, bilateral emphysema, and fibrotic changes, among others. Overall, an average of 86% agreement and 14% diagnostic discordance was determined between the two AI systems. The sensitivity of the AI system was 93% and the specificity 80% compared with RT-PCR. Conclusion: Paraguay has an AI-based telemedicine screening system for the rapid stratified detection of COVID-19 from chest CT images of patients with respiratory conditions. This application strengthens the integrated network of health services, rationalizing the use of specialized human resources, equipment, and inputs for laboratory diagnosis.

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