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Showing 1429 to 1438 of 1438 entries
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Coronavirus Disease 2019: Hysteresis Effect of Chest CT and the Correlation with its Severity.

Current medical imaging

Li K, Wang W, Wu L, Zhao C, Jiang Z, Liu S, Li T.
PMID: 34931984
Curr Med Imaging. 2021;17(12):1487-1495. doi: 10.2174/1573405617666210712162247.

PURPOSE: The purpose of this study was to investigate the influencing factors for chest CT hysteresis and severity of coronavirus disease 2019 (COVID-19).METHODS: The chest CT data of patients with confirmed COVID-19 in 4 hospitals were retrospectively analyzed. An...

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Li K, Wang W, Wu L, et al. Coronavirus Disease 2019: Hysteresis Effect of Chest CT and the Correlation with its Severity. Curr Med Imaging. 2021;17(12):1487-1495doi: 10.2174/1573405617666210712162247.
Li, K., Wang, W., Wu, L., Zhao, C., Jiang, Z., Liu, S., & Li, T. (2021). Coronavirus Disease 2019: Hysteresis Effect of Chest CT and the Correlation with its Severity. Current medical imaging, 17(12), 1487-1495. https://doi.org/10.2174/1573405617666210712162247
Li, Kui, et al. "Coronavirus Disease 2019: Hysteresis Effect of Chest CT and the Correlation with its Severity." Current medical imaging vol. 17,12 (2021): 1487-1495. doi: https://doi.org/10.2174/1573405617666210712162247
Li K, Wang W, Wu L, Zhao C, Jiang Z, Liu S, Li T. Coronavirus Disease 2019: Hysteresis Effect of Chest CT and the Correlation with its Severity. Curr Med Imaging. 2021;17(12):1487-1495. doi: 10.2174/1573405617666210712162247. PMID: 34931984.
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Optimal resection rate for lung cancer in the UK: how high should we go?.

BMJ open respiratory research

Belcher E, Mitchell J, Stavroulias D, Di Chiara F, Rahman N.
PMID: 34326151
BMJ Open Respir Res. 2021 Jul;8(1). doi: 10.1136/bmjresp-2020-000771.

BACKGROUND: The optimal resection rate for institutions managing early-stage primary lung cancer is not known. Whether the prognosis of patients who do not proceed to operation is determined by their comorbidities for which they were deemed at prohibitively high-operative...

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Belcher E, Mitchell J, Stavroulias D, et al. Optimal resection rate for lung cancer in the UK: how high should we go?. BMJ Open Respir Res. 2021;8(1)doi: 10.1136/bmjresp-2020-000771.
Belcher, E., Mitchell, J., Stavroulias, D., Di Chiara, F., & Rahman, N. (2021). Optimal resection rate for lung cancer in the UK: how high should we go?. BMJ open respiratory research, 8(1), . https://doi.org/10.1136/bmjresp-2020-000771
Belcher, Elizabeth, et al. "Optimal resection rate for lung cancer in the UK: how high should we go?." BMJ open respiratory research vol. 8,1 (2021). doi: https://doi.org/10.1136/bmjresp-2020-000771
Belcher E, Mitchell J, Stavroulias D, Di Chiara F, Rahman N. Optimal resection rate for lung cancer in the UK: how high should we go?. BMJ Open Respir Res. 2021 Jul;8(1). doi: 10.1136/bmjresp-2020-000771. PMID: 34326151; PMCID: PMC8323385.
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Intra-operative open-lung ventilatory strategy reduces postoperative complications after laparoscopic colorectal cancer resection: A randomised controlled trial.

European journal of anaesthesiology

Li H, Zheng ZN, Zhang NR, Guo J, Wang K, Wang W, Li LG, Jin J, Tang J, Liao YJ, Jin SQ.
PMID: 34366425
Eur J Anaesthesiol. 2021 Oct 01;38(10):1042-1051. doi: 10.1097/EJA.0000000000001580.

BACKGROUND: The role of the positive end-expiratory pressure (PEEP) and lung recruitment manoeuvre (LRM) combination (termed open-lung strategy, OLS) during intra-operative mechanical ventilation is not clear.OBJECTIVE: To determine whether an open-lung strategy constituting medium PEEP (6-8 cmH2O) and repeated...

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Li H, Zheng ZN, Zhang NR, et al. Intra-operative open-lung ventilatory strategy reduces postoperative complications after laparoscopic colorectal cancer resection: A randomised controlled trial. Eur J Anaesthesiol. 2021;38(10):1042-1051doi: 10.1097/EJA.0000000000001580.
Li, H., Zheng, Z. N., Zhang, N. R., Guo, J., Wang, K., Wang, W., Li, L. G., Jin, J., Tang, J., Liao, Y. J., & Jin, S. Q. (2021). Intra-operative open-lung ventilatory strategy reduces postoperative complications after laparoscopic colorectal cancer resection: A randomised controlled trial. European journal of anaesthesiology, 38(10), 1042-1051. https://doi.org/10.1097/EJA.0000000000001580
Li, Hong, et al. "Intra-operative open-lung ventilatory strategy reduces postoperative complications after laparoscopic colorectal cancer resection: A randomised controlled trial." European journal of anaesthesiology vol. 38,10 (2021): 1042-1051. doi: https://doi.org/10.1097/EJA.0000000000001580
Li H, Zheng ZN, Zhang NR, Guo J, Wang K, Wang W, Li LG, Jin J, Tang J, Liao YJ, Jin SQ. Intra-operative open-lung ventilatory strategy reduces postoperative complications after laparoscopic colorectal cancer resection: A randomised controlled trial. Eur J Anaesthesiol. 2021 Oct 01;38(10):1042-1051. doi: 10.1097/EJA.0000000000001580. PMID: 34366425; PMCID: PMC8452317.
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LGAN: Lung segmentation in CT scans using generative adversarial network.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society

Tan J, Jing L, Huo Y, Li L, Akin O, Tian Y.
PMID: 33278767
Comput Med Imaging Graph. 2021 Jan;87:101817. doi: 10.1016/j.compmedimag.2020.101817. Epub 2020 Nov 16.

Lung segmentation in Computerized Tomography (CT) images plays an important role in various lung disease diagnosis. Most of the current lung segmentation approaches are performed through a series of procedures with manually empirical parameter adjustments in each step. Pursuing...

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Tan J, Jing L, Huo Y, et al. LGAN: Lung segmentation in CT scans using generative adversarial network. Comput Med Imaging Graph. 2020;87:101817doi: 10.1016/j.compmedimag.2020.101817.
Tan, J., Jing, L., Huo, Y., Li, L., Akin, O., & Tian, Y. (2021). LGAN: Lung segmentation in CT scans using generative adversarial network. Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society, 87101817. https://doi.org/10.1016/j.compmedimag.2020.101817
Tan, Jiaxing, et al. "LGAN: Lung segmentation in CT scans using generative adversarial network." Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society vol. 87 (2021): 101817. doi: https://doi.org/10.1016/j.compmedimag.2020.101817
Tan J, Jing L, Huo Y, Li L, Akin O, Tian Y. LGAN: Lung segmentation in CT scans using generative adversarial network. Comput Med Imaging Graph. 2021 Jan;87:101817. doi: 10.1016/j.compmedimag.2020.101817. Epub 2020 Nov 16. PMID: 33278767; PMCID: PMC8477299.
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Ground-glass opacity (GGO): a review of the differential diagnosis in the era of COVID-19.

Japanese journal of radiology

Cozzi D, Cavigli E, Moroni C, Smorchkova O, Zantonelli G, Pradella S, Miele V.
PMID: 33900542
Jpn J Radiol. 2021 Aug;39(8):721-732. doi: 10.1007/s11604-021-01120-w. Epub 2021 Apr 26.

Thoracic imaging is fundamental in the diagnostic route of Coronavirus disease 2019 (COVID-19) especially in patients admitted to hospitals. In particular, chest computed tomography (CT) has a key role in identifying the typical features of the infection. Ground-glass opacities...

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Cozzi D, Cavigli E, Moroni C, et al. Ground-glass opacity (GGO): a review of the differential diagnosis in the era of COVID-19. Jpn J Radiol. 2021;39(8):721-732doi: 10.1007/s11604-021-01120-w.
Cozzi, D., Cavigli, E., Moroni, C., Smorchkova, O., Zantonelli, G., Pradella, S., & Miele, V. (2021). Ground-glass opacity (GGO): a review of the differential diagnosis in the era of COVID-19. Japanese journal of radiology, 39(8), 721-732. https://doi.org/10.1007/s11604-021-01120-w
Cozzi, Diletta, et al. "Ground-glass opacity (GGO): a review of the differential diagnosis in the era of COVID-19." Japanese journal of radiology vol. 39,8 (2021): 721-732. doi: https://doi.org/10.1007/s11604-021-01120-w
Cozzi D, Cavigli E, Moroni C, Smorchkova O, Zantonelli G, Pradella S, Miele V. Ground-glass opacity (GGO): a review of the differential diagnosis in the era of COVID-19. Jpn J Radiol. 2021 Aug;39(8):721-732. doi: 10.1007/s11604-021-01120-w. Epub 2021 Apr 26. PMID: 33900542; PMCID: PMC8071755.
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Alleviating Class-Wise Gradient Imbalance for Pulmonary Airway Segmentation.

IEEE transactions on medical imaging

Zheng H, Qin Y, Gu Y, Xie F, Yang J, Sun J, Yang GZ.
PMID: 33970858
IEEE Trans Med Imaging. 2021 Sep;40(9):2452-2462. doi: 10.1109/TMI.2021.3078828. Epub 2021 Aug 31.

Automated airway segmentation is a prerequisite for pre-operative diagnosis and intra-operative navigation for pulmonary intervention. Due to the small size and scattered spatial distribution of peripheral bronchi, this is hampered by a severe class imbalance between foreground and background...

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Zheng H, Qin Y, Gu Y, et al. Alleviating Class-Wise Gradient Imbalance for Pulmonary Airway Segmentation. IEEE Trans Med Imaging. 2021;40(9):2452-2462doi: 10.1109/TMI.2021.3078828.
Zheng, H., Qin, Y., Gu, Y., Xie, F., Yang, J., Sun, J., & Yang, G. Z. (2021). Alleviating Class-Wise Gradient Imbalance for Pulmonary Airway Segmentation. IEEE transactions on medical imaging, 40(9), 2452-2462. https://doi.org/10.1109/TMI.2021.3078828
Zheng, Hao, et al. "Alleviating Class-Wise Gradient Imbalance for Pulmonary Airway Segmentation." IEEE transactions on medical imaging vol. 40,9 (2021): 2452-2462. doi: https://doi.org/10.1109/TMI.2021.3078828
Zheng H, Qin Y, Gu Y, Xie F, Yang J, Sun J, Yang GZ. Alleviating Class-Wise Gradient Imbalance for Pulmonary Airway Segmentation. IEEE Trans Med Imaging. 2021 Sep;40(9):2452-2462. doi: 10.1109/TMI.2021.3078828. Epub 2021 Aug 31. PMID: 33970858.
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A commentary on "Moderate and severe exacerbations have a significant impact on health related quality of life, utility, and lung function in patients with chronic obstructive pulmonary disease: A meta-analysis" (Int J Surg 2020; 78:28-35).

International journal of surgery (London, England)

Li XM, Wang HX, Wang HY.
PMID: 33940198
Int J Surg. 2021 Jun;90:105961. doi: 10.1016/j.ijsu.2021.105961. Epub 2021 May 01.

No abstract available.

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Li XM, Wang HX, Wang HY. A commentary on "Moderate and severe exacerbations have a significant impact on health related quality of life, utility, and lung function in patients with chronic obstructive pulmonary disease: A meta-analysis" (Int J Surg 2020; 78:28-35). Int J Surg. 2021;90:105961doi: 10.1016/j.ijsu.2021.105961.
Li, X. M., Wang, H. X., & Wang, H. Y. (2021). A commentary on "Moderate and severe exacerbations have a significant impact on health related quality of life, utility, and lung function in patients with chronic obstructive pulmonary disease: A meta-analysis" (Int J Surg 2020; 78:28-35). International journal of surgery (London, England), 90105961. https://doi.org/10.1016/j.ijsu.2021.105961
Li, Xiao-Ming, et al. "A commentary on "Moderate and severe exacerbations have a significant impact on health related quality of life, utility, and lung function in patients with chronic obstructive pulmonary disease: A meta-analysis" (Int J Surg 2020; 78:28-35)." International journal of surgery (London, England) vol. 90 (2021): 105961. doi: https://doi.org/10.1016/j.ijsu.2021.105961
Li XM, Wang HX, Wang HY. A commentary on "Moderate and severe exacerbations have a significant impact on health related quality of life, utility, and lung function in patients with chronic obstructive pulmonary disease: A meta-analysis" (Int J Surg 2020; 78:28-35). Int J Surg. 2021 Jun;90:105961. doi: 10.1016/j.ijsu.2021.105961. Epub 2021 May 01. PMID: 33940198.
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Towards radiologist-level cancer risk assessment in CT lung screening using deep learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society

Trajanovski S, Mavroeidis D, Swisher CL, Gebre BG, Veeling BS, Wiemker R, Klinder T, Tahmasebi A, Regis SM, Wald C, McKee BJ, Flacke S, MacMahon H, Pien H.
PMID: 33895622
Comput Med Imaging Graph. 2021 Jun;90:101883. doi: 10.1016/j.compmedimag.2021.101883. Epub 2021 Mar 05.

PURPOSE: Lung cancer is the leading cause of cancer mortality in the US, responsible for more deaths than breast, prostate, colon and pancreas cancer combined and large population studies have indicated that low-dose computed tomography (CT) screening of the...

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Trajanovski S, Mavroeidis D, Swisher CL, et al. Towards radiologist-level cancer risk assessment in CT lung screening using deep learning. Comput Med Imaging Graph. 2021;90:101883doi: 10.1016/j.compmedimag.2021.101883.
Trajanovski, S., Mavroeidis, D., Swisher, C. L., Gebre, B. G., Veeling, B. S., Wiemker, R., Klinder, T., Tahmasebi, A., Regis, S. M., Wald, C., McKee, B. J., Flacke, S., MacMahon, H., & Pien, H. (2021). Towards radiologist-level cancer risk assessment in CT lung screening using deep learning. Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society, 90101883. https://doi.org/10.1016/j.compmedimag.2021.101883
Trajanovski, Stojan, et al. "Towards radiologist-level cancer risk assessment in CT lung screening using deep learning." Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society vol. 90 (2021): 101883. doi: https://doi.org/10.1016/j.compmedimag.2021.101883
Trajanovski S, Mavroeidis D, Swisher CL, Gebre BG, Veeling BS, Wiemker R, Klinder T, Tahmasebi A, Regis SM, Wald C, McKee BJ, Flacke S, MacMahon H, Pien H. Towards radiologist-level cancer risk assessment in CT lung screening using deep learning. Comput Med Imaging Graph. 2021 Jun;90:101883. doi: 10.1016/j.compmedimag.2021.101883. Epub 2021 Mar 05. PMID: 33895622.
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Internet of Medical Things: An Effective and Fully Automatic IoT Approach Using Deep Learning and Fine-Tuning to Lung CT Segmentation.

Sensors (Basel, Switzerland)

Souza LFF, Silva ICL, Marques AG, Silva FHDS, Nunes VX, Hassan MM, Albuquerque VHC, Filho PPR.
PMID: 33255308
Sensors (Basel). 2020 Nov 24;20(23). doi: 10.3390/s20236711.

Several pathologies have a direct impact on society, causing public health problems. Pulmonary diseases such as Chronic obstructive pulmonary disease (COPD) are already the third leading cause of death in the world, leaving tuberculosis at ninth with 1.7 million...

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Souza LFF, Silva ICL, Marques AG, et al. Internet of Medical Things: An Effective and Fully Automatic IoT Approach Using Deep Learning and Fine-Tuning to Lung CT Segmentation. Sensors (Basel). 2020;20(23)doi: 10.3390/s20236711.
Souza, L. F. F., Silva, I. C. L., Marques, A. G., Silva, F. H. D. S., Nunes, V. X., Hassan, M. M., Albuquerque, V. H. C., & Filho, P. P. R. (2020). Internet of Medical Things: An Effective and Fully Automatic IoT Approach Using Deep Learning and Fine-Tuning to Lung CT Segmentation. Sensors (Basel, Switzerland), 20(23), . https://doi.org/10.3390/s20236711
Souza, Luís Fabrício de Freitas, et al. "Internet of Medical Things: An Effective and Fully Automatic IoT Approach Using Deep Learning and Fine-Tuning to Lung CT Segmentation." Sensors (Basel, Switzerland) vol. 20,23 (2020). doi: https://doi.org/10.3390/s20236711
Souza LFF, Silva ICL, Marques AG, Silva FHDS, Nunes VX, Hassan MM, Albuquerque VHC, Filho PPR. Internet of Medical Things: An Effective and Fully Automatic IoT Approach Using Deep Learning and Fine-Tuning to Lung CT Segmentation. Sensors (Basel). 2020 Nov 24;20(23). doi: 10.3390/s20236711. PMID: 33255308; PMCID: PMC7727680.
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Coronavirus disease 2019 and the gut-lung axis.

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases

Zhou D, Wang Q, Liu H.
PMID: 34517046
Int J Infect Dis. 2021 Dec;113:300-307. doi: 10.1016/j.ijid.2021.09.013. Epub 2021 Sep 10.

Gastrointestinal and respiratory tract diseases often occur together. There are many overlapping pathologies, leading to the concept of the 'gut-lung axis' in which stimulation on one side triggers a response on the other side. This axis appears to be...

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Zhou D, Wang Q, Liu H. Coronavirus disease 2019 and the gut-lung axis. Int J Infect Dis. 2021;113:300-307doi: 10.1016/j.ijid.2021.09.013.
Zhou, D., Wang, Q., & Liu, H. (2021). Coronavirus disease 2019 and the gut-lung axis. International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases, 113300-307. https://doi.org/10.1016/j.ijid.2021.09.013
Zhou, Dan, et al. "Coronavirus disease 2019 and the gut-lung axis." International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases vol. 113 (2021): 300-307. doi: https://doi.org/10.1016/j.ijid.2021.09.013
Zhou D, Wang Q, Liu H. Coronavirus disease 2019 and the gut-lung axis. Int J Infect Dis. 2021 Dec;113:300-307. doi: 10.1016/j.ijid.2021.09.013. Epub 2021 Sep 10. PMID: 34517046; PMCID: PMC8431834.
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Showing 1429 to 1438 of 1438 entries