Machine learning predicts x-ray pulse properties from XFEL parameters.
problem Characterizing XFEL pulses for sorting data due to large fluctuations.
method Applied machine learning to predict x-ray pulse properties using electron beam and x-ray parameters.
result Mean errors below 0.3 eV for photon energy and below 1.6 fs for delay between pulses at 530 eV.
Deep chest X-ray classifiers show bias in predicting diagnoses.
problem Bias in deep learning classifiers predicting diagnoses from chest X-rays.
method Trained convolutional neural networks on multiple public datasets to predict 14 diagnostic labels.
result True positive rates vary significantly among different protected attributes, indicating bias.
Deep learning system detects hip fractures as well as radiologists.
problem Automatically identifying hip fractures from x-rays.
method Trained on 53,000 clinical x-rays, system achieves 0.994 ROC curve.
result Equivalent diagnostic performance to human radiologists.
Deep learning model performs differently in TB-specific vs non-TB-specific chest X-rays.
problem Limited generalizability of machine learning models for tuberculosis detection.
method Developed a DCNN model using a TB-specific CXR dataset and tested it on a non-TB-specific CXR dataset.
result A deep learning model trained on one population's TB CXR data does not generalize well to another population.
Study shows cross-domain X-ray prediction performance discrepancies and label shifts.
problem Quantifying generalization limits across different X-ray datasets.
method Large-scale study on multiple X-ray datasets, focusing on performance and label shifts.
result Interesting discrepancies found between model performance and agreement, and concept similarity across tasks.
Paper uses deep learning to suppress bones on chest X-rays.
problem Improving pathologies classification by suppressing bones on chest X-rays.
method Conditional Generative Adversarial Network (GAN) and Haar 2D wavelet decomposition.
result Achieves state-of-the-art performance on bone suppression.
Bayesian CNN estimates uncertainty in COVID-19 detection.
problem Uncertainty in deep learning predictions for medical diagnosis.
method Drop-weight based Bayesian Convolutional Neural Networks (BCNN).
result Uncertainty correlates with prediction accuracy.
GraphXCOVID uses deep semi-supervised learning to identify COVID-19 from chest X-rays with minimal labels.
problem Identifying COVID-19 on chest X-rays with limited labelled data.
method Graph-based deep semi-supervised framework with pseudo-labeling and attention maps.
result Outperforms current supervised models with a tiny fraction of labelled examples.
Novel method separates astrophysical components from noisy data.
problem Separating and reconstructing astrophysical components from noisy data.
method Latent-space field tension for automated component separation.
result High accuracy in reconstructing astrophysical components.
Smartphone app diagnoses pulmonary diseases from chest X-rays.
problem Scarcity of training data and class imbalance issues.
method Data Augmentation Generative Adversarial Network (DAGAN) and Convolutional Siamese Network with attention mechanism.
result Achieved 99.30% and 98.40% testing accuracy on Binary/Multiclass scenarios.
This paper benchmarks OoDD methods for medical imaging.
problem Medical models trained for one domain may fail on images from a different domain.
method Defined 3 categories of OoD examples and benchmarked methods in 3 medical imaging domains.
result Simple binary classifier on feature representation yields best accuracy and AUPRC.
Lecture notes on analysis tools for X-ray tomography.
problem Understanding X-ray tomography using mathematical analysis.
method Overview of analysis tools and ideas, minimal assumptions.
result Broad overview of analysis tools for X-ray tomography.
Sharp mapping properties and regularization for X-ray transform on disks of constant curvature.
problem Sharp mapping properties and regularization of X-ray transform.
method Derive functional relations and mapping properties using elliptic differential operators.
result Theoretical possibility of regularized inversions for X-ray transform.
CNNs trained on one hospital's x-rays perform poorly on x-rays from other hospitals.
problem Generalization of radiological deep learning models across different hospitals.
method Cross-sectional design using x-rays from three hospitals (NIH, Mount Sinai, Indiana).
result CNNs trained on one hospital's x-rays perform significantly worse on x-rays from other hospitals.
Regularity results for geodesic X-ray transform on nonsmooth manifolds
problem Geodesic X-ray transform on nonsmooth simple manifolds
method Symbol smoothing arguments and pseudodifferential operators with low regularity symbols
result Improved injectivity results for Lp functions Paper shows invertibility of tensor X-ray transform on certain manifolds.
problem Invertibility of tensor X-ray transform on asymptotically conic manifolds.
method Used 1-cusp pseudodifferential operator algebra and modified solenoidal gauge condition.
result Invertibility of tensor X-ray transform up to natural obstruction.
Local X-ray transform works well near boundaries in hyperbolic spaces.
problem Injectivity of X-ray transform near boundaries for hyperbolic metrics.
method Local injectivity proof for geodesic X-ray transform on asymptotically hyperbolic manifolds.
result Local injectivity near a boundary point for X-ray transform in dimensions 3 and higher, up to O(ρ5). Study characterizes X-ray transform kernel for periodic slabs and related manifolds.
problem Characterizing the kernel of X-ray transform for tensor fields on periodic slabs.
method Characterization of the kernel for L2-regular m-tensors on [0,1]imesTn. result Kernel characterization extends to more general manifolds, including the Möbius strip.
Model learns to focus on key areas of chest X-rays.
problem Detecting abnormalities in chest X-rays.
method Recurrent visual attention model using reinforcement learning.
result Model can focus on informative areas of X-rays.
Functions with constant geodesic X-ray transform are restricted to manifolds with specific geometrical properties.
problem Existence of functions with constant geodesic X-ray transform on manifolds.
method Analyzing the geometrical properties of manifolds based on the existence of such functions.
result Functions with constant geodesic X-ray transform impose specific geometrical restrictions on the manifold.
Study shows X-ray transform injectivity for hyperbolic manifolds.
problem Recovering metrics from boundary measurements on hyperbolic manifolds.
method Injectivity of X-ray transform in several cases.
result Injectivity of X-ray transform proven for asymptotically hyperbolic manifolds.
ECS evaluates synthetic CXR images' distributional fidelity.
problem Evaluating synthetic CXR images' distributional fidelity under privacy constraints.
method Characteristic function transforms of feature embeddings.
result ECS uncovers clinically relevant distributional discrepancies.
Study shows stability in X-ray transform on specific hyperbolic manifolds.
problem Stability of X-ray transform on asymptotically hyperbolic manifolds.
method Constructed a parametrix for the normal operator in 0-pseudodifferential calculus.
result Showed a stability estimate for the X-ray transform.
Study X-ray transform on Anosov manifolds with improved stability estimates.
problem Analyzing the geodesic X-ray transform on Anosov manifolds.
method Refined Livsic theorem for Anosov flows, new quantitative finite time Livsic theorem.
result New stability estimates for the X-ray transform.
Deep learning tackles X-ray noise without clean data.
problem Lack of clean X-ray images for deep learning denoising.
method Uses Stein's Unbiased Risk Estimator (SURE) to train a deep neural network.
result SURE-based approach effectively denoises X-ray images.
CheXNet detects pneumonia from chest X-rays better than radiologists.
problem Detecting pneumonia from chest X-rays with high accuracy.
method 121-layer convolutional neural network trained on ChestX-ray14 dataset.
result CheXNet outperforms radiologists on F1 metric.
Study X-ray transform on conic spaces, proving injectivity under certain conditions.
problem Injectivity of geodesic X-ray transform on conic metrics.
method Injectivity under non-trapping and no conjugate point assumptions.
result Injectivity of geodesic X-ray transform for asymptotically conic metrics.
Injectivity of X-ray transform on solenoidal tensors proven for certain manifolds.
problem Injectivity of X-ray transform on solenoidal tensors on manifolds with hyperbolic trapped set.
method Proof of equivalence principle concerning injectivity and surjectivity of operators on symmetric solenoidal tensors.
result Injectivity of X-ray transform on solenoidal tensors of any order for surfaces with hyperbolic trapped set.
Injective X-ray transform on Heisenberg group for regular functions.
problem Injectivity of X-ray transform on sub-Riemannian manifolds.
method Group Fourier Transform and analysis of taming metrics.
result Sufficiently regular functions on Heisenberg group are determined by their line integrals.
Paper proves injectivity of non-abelian X-ray transform on certain spaces.
problem Injectivity of non-abelian X-ray transform on asymptotically hyperbolic spaces.
method Gauge equivalence for unitary connections and skew-Hermitian Higgs fields.
result Injectivity result for non-abelian X-ray transform over skew-Hermitian Higgs fields.
Large dataset study improves chest x-ray analysis.
problem Improving accuracy in recognizing thorax diseases from chest x-rays.
method Training and evaluating deep convolutional neural networks (CNNs) on a large dataset (473k images).
result DualNet architecture shows improved performance in recognizing chest x-ray findings.
Deep-learning method estimates bone 3D structure from X-ray images.
problem Estimating bone 3D structure from X-ray images.
method Triplet loss-trained neural network selecting closest 3D bone shape from predefined set.
result Average RMS distance of 1.08 mm between predicted and true shapes.
X-ray transform on H-type groups solved, revealing function injectivity.
problem Injectivity in sub-Riemannian geometry.
method Fourier Slice Theorem adapted to H-type groups.
result Integrable functions on H-type groups are uniquely determined by their integrals over geodesics.
New method eliminates domain size restrictions for X-ray transform inversion.
problem Injectivity and stability of X-ray transform in convex domains.
method Semiclassical analysis to invert X-ray transform without small domain assumptions.
result Elimination of domain size restrictions for injectivity and stability.
Study improves deep learning chest X-ray models by incorporating lateral views.
problem Lack of lateral views in training datasets limits deep learning performance.
method Used PadChest dataset with multiple views to explore merging methods.
result Incorporating lateral views increases model performance for 32 labels.
Study proper sampling for X-ray transforms on simple surfaces.
problem Proper discretizing and sampling issues related to geodesic X-ray transforms on simple surfaces.
method Provide minimal sampling rates for faithful reconstruction, quantify sampling quality, and predict artifacts.
result Minimal sampling rates and artifact prediction for geodesic X-ray transforms on simple surfaces.
FRODO method rejects out-of-distribution chest x-ray images with high accuracy.
problem Rejecting out-of-distribution samples in medical image analysis.
method Uses feature activations and Mahalanobis distance to measure distribution mismatch.
result Achieves an AUC score of 0.99 in classifying chest x-ray images as in or out of distribution.
New proof of injectivity for broken non-abelian X-ray transform in Minkowski space.
problem Injectivity of broken non-abelian X-ray transform in Minkowski space.
method Stability estimate considering gauge, light-sink connections, Bayesian inversion.
result Consistent recovery of light-sink connections from noisy data.
Paper solves injectivity of X-ray transform on surfaces.
problem Injectivity of non-Abelian X-ray transform on surfaces.
method Factorization theorem for Loop Groups, energy methods, scalar holomorphic integrating factors.
result Extends results to arbitrary Lie groups.
Enhanced X-ray polarimetry with deep learning for better exposure times.
problem Improving sensitivity of X-ray telescopic observations with imaging polarimeters.
method A weighted maximum likelihood combination of predictions from a deep ensemble of ResNet convolutional neural networks trained on Monte Carlo event simulations.
result Improves effective exposure times by ~45% for power-law source spectra.
Study X-ray transform on manifolds, desingularize, and improve mapping properties.
problem Characterize mapping properties of X-ray transform and its adjoint on manifolds with strictly convex boundary.
method Use b-fibrations, desingularize, and apply Melrose's Pushforward Theorem to analyze polyhomogeneous functions.
result Improved mapping properties of X-ray transform and its adjoint, recovering sharp results.
Unique continuation for X-ray transforms of one-forms with partial data.
problem Proving unique continuation for X-ray transforms of one-forms with limited data.
method Proved unique continuation for the normal operator of X-ray transforms of one-forms, leading to partial data results.
result Unique continuation for X-ray transforms of one-forms with partial data.
Study shows certain manifolds uniquely determined by X-ray data.
problem Determining manifolds from X-ray data.
method Injectivity of X-ray transform over symmetric solenoidal 2-tensors.
result Smooth compact manifolds with strictly convex boundary, no conjugate points, and hyperbolic trapped set are locally marked boundary rigid.
Support theorem proved for X-ray transform on certain non-compact manifolds.
problem Support theorem for X-ray transform on non-compact manifolds with conjugate points.
method Use of plane covers and support theorem for simple manifolds by Krishnan.
result Support theorem proved for simply connected 2-step nilpotent Lie groups and some non-homogeneous 3D manifolds.
Guillarmou extends X-ray transform to magnetic and thermostat flows.
problem Stability of magnetic X-ray transforms.
method Generalizes normal operator to thermostat and magnetic flows, proving ellipticity.
result Elliptic pseudodifferential operators of order -1 for generalized normal operators.
New insights into X-ray transform on hyperbolic disk, with functional relations and range characterizations.
problem Understanding the X-ray transform on hyperbolic geometry.
method Derived new singular value decompositions, range characterizations, and intertwining relations with wedge-type differential operators.
result Sharp understanding of boundary behavior and invertibility settings for the X-ray transform.
Novel semi-supervised method for X-ray classification with minimal labels.
problem Classifying X-ray data with limited labeled data.
method Graph-based semi-supervised learning with carefully selected class priors.
result Competitive results on ChestX-ray14 data set with reduced need for annotated data.
Paper shows X-ray transform invertible on certain curved spaces.
problem Invertibility of X-ray transform on curved spaces.
method Introduced new pseudodifferential operator algebra for analysis.
result Stable invertibility near infinity on asymptotically conic manifolds.