An efficient deep learning approach to pneumonia classification in healthcare
This study proposes a convolutional neural network model trained from scratch to classify
and detect the presence of pneumonia from a collection of chest X‐ray image samples …
and detect the presence of pneumonia from a collection of chest X‐ray image samples …
Efficient pneumonia detection in chest xray images using deep transfer learning
Pneumonia causes the death of around 700,000 children every year and affects 7% of the
global population. Chest X-rays are primarily used for the diagnosis of this disease …
global population. Chest X-rays are primarily used for the diagnosis of this disease …
CDC_Net: Multi-classification convolutional neural network model for detection of COVID-19, pneumothorax, pneumonia, lung Cancer, and tuberculosis using chest X …
Abstract Coronavirus (COVID-19) has adversely harmed the healthcare system and
economy throughout the world. COVID-19 has similar symptoms as other chest disorders …
economy throughout the world. COVID-19 has similar symptoms as other chest disorders …
Learning to read chest x-rays: Recurrent neural cascade model for automated image annotation
Despite the recent advances in automatically describing image contents, their applications
have been mostly limited to image caption datasets containing natural images (eg, Flickr …
have been mostly limited to image caption datasets containing natural images (eg, Flickr …
Multi-resolution convolutional networks for chest X-ray radiograph based lung nodule detection
Lung cancer is the leading cause of cancer death worldwide. Early detection of lung cancer
is helpful to provide the best possible clinical treatment for patients. Due to the limited …
is helpful to provide the best possible clinical treatment for patients. Due to the limited …
Isotropic total variation regularization of displacements in parametric image registration
V Vishnevskiy, T Gass, G Szekely… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
Spatial regularization is essential in image registration, which is an ill-posed problem.
Regularization can help to avoid both physically implausible displacement fields and local …
Regularization can help to avoid both physically implausible displacement fields and local …
Accurate point cloud registration with robust optimal transport
This work investigates the use of robust optimal transport (OT) for shape matching.
Specifically, we show that recent OT solvers improve both optimization-based and deep …
Specifically, we show that recent OT solvers improve both optimization-based and deep …
Estimation of large motion in lung CT by integrating regularized keypoint correspondences into dense deformable registration
We present a novel algorithm for the registration of pulmonary CT scans. Our method is
designed for large respiratory motion by integrating sparse keypoint correspondences into a …
designed for large respiratory motion by integrating sparse keypoint correspondences into a …
An efficient ensemble method for detecting spinal curvature type using deep transfer learning and soft voting classifier
P Tavana, M Akraminia, A Koochari… - Expert Systems with …, 2023 - Elsevier
Scoliosis is a spinal deformity that negatively affects the body's distribution of weight in
several ways. This deformity can be classified as C-shaped or S-shaped. These deformities …
several ways. This deformity can be classified as C-shaped or S-shaped. These deformities …
Robust non-rigid point set registration using spatially constrained Gaussian fields
Estimating transformations from degraded point sets is necessary for many computer vision
and pattern recognition applications. In this paper, we propose a robust non-rigid point set …
and pattern recognition applications. In this paper, we propose a robust non-rigid point set …