Evaluation of emphysema on thoracic low-dose CTs through attention-based multiple instance deep learning
In addition to lung cancer, other thoracic abnormalities, such as emphysema, can be
visualized within low-dose CT scans that were initially obtained in cancer screening …
visualized within low-dose CT scans that were initially obtained in cancer screening …
CT-based COPD identification using multiple instance learning with two-stage attention
M Xue, S Jia, L Chen, H Huang, L Yu, W Zhu - Computer Methods and …, 2023 - Elsevier
Background and objective Chronic obstructive pulmonary disease (COPD) is one of the
leading causes of morbidity and mortality worldwide. However, COPD remains …
leading causes of morbidity and mortality worldwide. However, COPD remains …
Lung cancer diagnosis using deep attention‐based multiple instance learning and radiomics
Background Early diagnosis of lung cancer is a key intervention for the treatment of lung
cancer in which computer‐aided diagnosis (CAD) can play a crucial role. Most published …
cancer in which computer‐aided diagnosis (CAD) can play a crucial role. Most published …
Attention based deep multiple instance learning approach for lung cancer prediction using histopathological images
J Moranguinho, T Pereira, B Ramos… - 2021 43rd Annual …, 2021 - ieeexplore.ieee.org
Deep Neural Networks using histopathological images as an input currently embody one of
the gold standards in automated lung cancer diagnostic solutions, with Deep Convolutional …
the gold standards in automated lung cancer diagnostic solutions, with Deep Convolutional …
Detecting emphysema with multiple instance learning
SN Ørting, J Petersen, LH Thomsen… - 2018 IEEE 15th …, 2018 - ieeexplore.ieee.org
Emphysema is part of chronic obstructive pulmonary disease, a leading cause of mortality
worldwide. Visual assessment of emphysema presence is useful for identifying subjects at …
worldwide. Visual assessment of emphysema presence is useful for identifying subjects at …
Multiple instance learning for malignant vs. benign classification of lung nodules in thoracic screening ct data
W Safta, MM Farhangi, B Veasey… - 2019 IEEE 16Th …, 2019 - ieeexplore.ieee.org
Multiple Instance Learning (MIL) is proposed for Computer Aided Diagnosis (CADx) without
predefined Regions Of Interest (ROIs) from lung cancer screening thoracic CT scans. The …
predefined Regions Of Interest (ROIs) from lung cancer screening thoracic CT scans. The …
DR-MIL: deep represented multiple instance learning distinguishes COVID-19 from community-acquired pneumonia in CT images
Background and objective Given that the novel coronavirus disease 2019 (COVID-19) has
become a pandemic, a method to accurately distinguish COVID-19 from community …
become a pandemic, a method to accurately distinguish COVID-19 from community …
Relational learning between multiple pulmonary nodules via deep set attention transformers
Diagnosis and treatment of multiple pulmonary nodules are clinically important but
challenging. Prior studies on nodule characterization use solitary-nodule approaches on …
challenging. Prior studies on nodule characterization use solitary-nodule approaches on …
Hierarchical attention-based multiple instance learning network for patient-level lung cancer diagnosis
Q Wang, Y Zhou, J Huang, Z Liu, L Li… - 2020 IEEE …, 2020 - ieeexplore.ieee.org
Lung cancer is the leading cause of cancer-related deaths worldwide, while the risk factors
for lung cancer mortality can be significantly reduced if the accurate early diagnoses for …
for lung cancer mortality can be significantly reduced if the accurate early diagnoses for …
Dual attention multiple instance learning with unsupervised complementary loss for COVID-19 screening
Chest computed tomography (CT) based analysis and diagnosis of the Coronavirus Disease
2019 (COVID-19) plays a key role in combating the outbreak of the pandemic that has …
2019 (COVID-19) plays a key role in combating the outbreak of the pandemic that has …