MSF-Net: a lightweight multi-scale feature fusion network for skin lesion segmentation
D Shao, L Ren, L Ma - Biomedicines, 2023 - mdpi.com
Segmentation of skin lesion images facilitates the early diagnosis of melanoma. However,
this remains a challenging task due to the diversity of target scales, irregular segmentation …
this remains a challenging task due to the diversity of target scales, irregular segmentation …
[HTML][HTML] Exploring the efficacy of artificial neural networks in predicting lung cancer recurrence: a retrospective study based on patient records
A Lorenc, A Romaszko-Wojtowicz… - Translational Lung …, 2023 - ncbi.nlm.nih.gov
Background Lung cancer remains a significant public health concern, accounting for a
considerable number of cancer-related deaths worldwide. Neural networks have emerged …
considerable number of cancer-related deaths worldwide. Neural networks have emerged …
Can Artificial Intelligence Replace Humans for Detecting Lung Tumors on Radiographs? An Examination of Resected Malignant Lung Tumors
R Hamanaka, M Oda - Journal of Personalized Medicine, 2024 - mdpi.com
Objective: Although lung cancer screening trials have showed the efficacy of computed
tomography to decrease mortality compared with chest radiography, the two are widely …
tomography to decrease mortality compared with chest radiography, the two are widely …
[PDF][PDF] The potential role of artificial intelligence-assisted chest X-ray imaging in detecting early-stage lung cancer in the community—a proposed algorithm for lung …
Introduction: The poor prognosis of lung cancer has been largely attributed to the fact that
most patients present with advanced stage disease. Although low dose computed …
most patients present with advanced stage disease. Although low dose computed …
Usefulness of copper filters in digital chest radiography based on the relationship between effective detective quantum efficiency and deep learning-based …
S Onodera, Y Kondo, S Ishizawa, T Kawabata… - … Physics and Technology, 2023 - Springer
This study aimed to determine the optimal radiographic conditions for detecting lesions on
digital chest radiographs using an indirect conversion flat-panel detector with a copper (Cu) …
digital chest radiographs using an indirect conversion flat-panel detector with a copper (Cu) …
[HTML][HTML] Oncology in the modern era: Artificial Intelligence is reshaping cancer diagnosis, prognosis and treatment
M Delshad, MA Omrani, A Pourbagheri-Sigaroodi… - Iranian Journal of Blood …, 2023 - ijbc.ir
The field of cancer research has been profoundly impacted by the utilization of artificial
intelligence (AI), particularly through the analysis of medical records encompassing …
intelligence (AI), particularly through the analysis of medical records encompassing …
[PDF][PDF] Automatic lung segmentation in chest X-ray images using SAM with prompts from YOLO
E Khalili, B Priego-Torres, A Leon-Jimenez… - Authorea …, 2024 - techrxiv.org
Despite the impressive performance of current deep learning models in the field of medical
imaging, the transfer of the lung segmentation task in X-ray images to clinical practice is still …
imaging, the transfer of the lung segmentation task in X-ray images to clinical practice is still …
Machine learning for non-invasive tissue characterization in body imaging
Y Yin - 2023 - research.rug.nl
Tissue characterization plays a vital role in the diagnosis of various diseases, as it involves
the analysis of the structural, biochemical, and physiological properties of tissues to …
the analysis of the structural, biochemical, and physiological properties of tissues to …
Enhancing Early Detection of Lung Cancer Through Advanced Medical Imaging and Automation: A Focus on CT scans
G Preetha, SNS Rajini… - 2023 9th International …, 2023 - ieeexplore.ieee.org
Lung cancer remains the leading cause of cancer-related deaths globally, highlighting the
need to focus on early detection and prognosis. This research paper addresses the …
need to focus on early detection and prognosis. This research paper addresses the …