AI-based improvement in lung cancer detection on chest radiographs: results of a multi-reader study in NLST dataset
Objective Assess if deep learning–based artificial intelligence (AI) algorithm improves
reader performance for lung cancer detection on chest X-rays (CXRs). Methods This reader …
reader performance for lung cancer detection on chest X-rays (CXRs). Methods This reader …
MuSiC-ViT: A multi-task Siamese convolutional vision transformer for differentiating change from no-change in follow-up chest radiographs
A major responsibility of radiologists in routine clinical practice is to read follow-up chest
radiographs (CXRs) to identify changes in a patient's condition. Diagnosing meaningful …
radiographs (CXRs) to identify changes in a patient's condition. Diagnosing meaningful …
Enhancing the performance of premature ventricular contraction detection in unseen datasets through deep learning with denoise and contrast attention module
Premature ventricular contraction (PVC) is a common and harmless cardiac arrhythmia that
can be asymptomatic or cause palpitations and chest pain in rare instances. However …
can be asymptomatic or cause palpitations and chest pain in rare instances. However …
Asymmetry disentanglement network for interpretable acute ischemic stroke infarct segmentation in non-contrast CT scans
Accurate infarct segmentation in non-contrast CT (NCCT) images is a crucial step toward
computer-aided acute ischemic stroke (AIS) assessment. In clinical practice, bilateral …
computer-aided acute ischemic stroke (AIS) assessment. In clinical practice, bilateral …
Performance of a deep-learning algorithm for referable thoracic abnormalities on chest radiographs: A multicenter study of a health screening cohort
Purpose This study evaluated the performance of a commercially available deep-learning
algorithm (DLA)(Insight CXR, Lunit, Seoul, South Korea) for referable thoracic abnormalities …
algorithm (DLA)(Insight CXR, Lunit, Seoul, South Korea) for referable thoracic abnormalities …
Module of Axis-based Nexus Attention for weakly supervised object localization
Weakly supervised object localization tasks remain challenging to identify and segment an
entire object rather than only discriminative parts of the object. To tackle this problem …
entire object rather than only discriminative parts of the object. To tackle this problem …
[CITATION][C] Development and validation of a deep learning algorithm detecting 10 common abnormalities on chest radiographs
Foliage-Pattern-Identifier: A Hybridized Grey Wolf & Adam optimized Deep Learning architecture designed for identification of similarly patterned leaves
S Banerjee, SKD Hassan, S Mukherjee… - … on Image Processing …, 2023 - ieeexplore.ieee.org
Automated leaf pattern identification has emerged as a prominent research area in the field
of computer vision, given the crucial role of leaves in monitoring plant health. Recognizing …
of computer vision, given the crucial role of leaves in monitoring plant health. Recognizing …
MLing-Net: A computationally inexpensive deep neural framework designed to perform multilingual image document classification
S Banerjee, D Shende - 2023 7th International Conference on …, 2023 - ieeexplore.ieee.org
Multilingual image document classification has become an emerging research topic in the
present era because of immense social, economic, and cultural perspectives. It supports …
present era because of immense social, economic, and cultural perspectives. It supports …
GreenMedNet: A computationally inexpensive hyperparameter optimised dual attention based insulin leaves categorization approach
Automated classification of distinct leaf categories through advanced deep neural
technologies has emerged as a notable research trend. The primary aim of this research is …
technologies has emerged as a notable research trend. The primary aim of this research is …