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Found 34 papers, 5 papers with code
Example-Guided Image Synthesis using Masked Spatial-Channel Attention and Self-Supervision
Example-guided image synthesis has recently been attempted to synthesize an image from a semantic label map and an exemplary image.
DocTr: Document Transformer for Structured Information Extraction in Documents
We present a new formulation for structured information extraction (SIE) from visually rich documents.
Ranked #3 on
Entity Linking
on FUNSD
REGAS: REspiratory-GAted Synthesis of Views for Multi-Phase CBCT Reconstruction from a single 3D CBCT Acquisition
It is a long-standing challenge to reconstruct Cone Beam Computed Tomography (CBCT) of the lung under respiratory motion.
Breast Cancer Induced Bone Osteolysis Prediction Using Temporal Variational Auto-Encoders
Its ability of predicting the development of bone lesions in cancer-invading bones can assist in assessing the risk of impending fractures and choosing proper treatments in breast cancer bone metastasis.
Learning Bias-Invariant Representation by Cross-Sample Mutual Information Minimization
We propose to remove the bias information misused by the target task with a cross-sample adversarial debiasing (CSAD) method.
Visual Relationship Detection Using Part-and-Sum Transformers with Composite Queries
Computer vision applications such as visual relationship detection and human object interaction can be formulated as a composite (structured) set detection problem in which both the parts (subject, object, and predicate) and the sum (triplet as a whole) are to be detected in a hierarchical fashion.
XraySyn: Realistic View Synthesis From a Single Radiograph Through CT Priors
A radiograph visualizes the internal anatomy of a patient through the use of X-ray, which projects 3D information onto a 2D plane.
A Smartphone-based System for Real-time Early Childhood Caries Diagnosis
The identification of ECC in an early stage usually requires expertise in the field, and hence is often ignored by parents.
Alleviating the Incompatibility between Cross Entropy Loss and Episode Training for Few-shot Skin Disease Classification
Inspired by the recent success of Few-Shot Learning (FSL) in natural image classification, we propose to apply FSL to skin disease identification to address the extreme scarcity of training sample problem.
Example-Guided Image Synthesis across Arbitrary Scenes using Masked Spatial-Channel Attention and Self-Supervision
Example-guided image synthesis has recently been attempted to synthesize an image from a semantic label map and an exemplary image.
Structured Landmark Detection via Topology-Adapting Deep Graph Learning
Image landmark detection aims to automatically identify the locations of predefined fiducial points.
Ranked #4 on
Face Alignment
on COFW-68
Unsupervised Learning of Landmarks based on Inter-Intra Subject Consistencies
To recover from the transformed images back to the original subject, the landmark detector is forced to learn spatial locations that contain the consistent semantic meanings both for the paired intra-subject images and between the paired inter-subject images.
A$^3$DSegNet: Anatomy-aware artifact disentanglement and segmentation network for unpaired segmentation, artifact reduction, and modality translation
In contrast, there exists a wealth of artifact-free, high quality CT images with vertebra annotations.
Encoding Metal Mask Projection for Metal Artifact Reduction in Computed Tomography
Metal artifact reduction (MAR) in computed tomography (CT) is a notoriously challenging task because the artifacts are structured and non-local in the image domain.
Example-Guided Scene Image Synthesis using Masked Spatial-Channel Attention and Patch-Based Self-Supervision
Example-guided image synthesis has been recently attempted to synthesize an image from a semantic label map and an exemplary image.
Deep Slice Interpolation via Marginal Super-Resolution, Fusion and Refinement
We propose a marginal super-resolution (MSR) approach based on 2D convolutional neural networks (CNNs) for interpolating an anisotropic brain magnetic resonance scan along the highly under-sampled direction, which is assumed to axial without loss of generality.
ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction
Current deep neural network based approaches to computed tomography (CT) metal artifact reduction (MAR) are supervised methods that rely on synthesized metal artifacts for training.
Automatic Radiology Report Generation based on Multi-view Image Fusion and Medical Concept Enrichment
In addition, in order to enrich the decoder with descriptive semantics and enforce the correctness of the deterministic medical-related contents such as mentions of organs or diagnoses, we extract medical concepts based on the radiology reports in the training data and fine-tune the encoder to extract the most frequent medical concepts from the x-ray images.
Generative Mask Pyramid Network for CT/CBCT Metal Artifact Reduction with Joint Projection-Sinogram Correction
A conventional approach to computed tomography (CT) or cone beam CT (CBCT) metal artifact reduction is to replace the X-ray projection data within the metal trace with synthesized data.
DuDoNet: Dual Domain Network for CT Metal Artifact Reduction
The linkage between the sigogram and image domains is a novel Radon inversion layer that allows the gradients to back-propagate from the image domain to the sinogram domain during training.
Patch Transformer for Multi-tagging Whole Slide Histopathology Images
Automated whole slide image (WSI) tagging has become a growing demand due to the increasing volume and diversity of WSIs collected nowadays in histopathology.
Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction
Extensive experiments show that our method significantly outperforms the existing unsupervised models for image-to-image translation problems, and achieves comparable performance to existing supervised models on a synthesized dataset.
Multiview 2D/3D Rigid Registration via a Point-Of-Interest Network for Tracking and Triangulation
As the POI tracker is shift-invariant, POINT^2 is more robust to the initial pose of the 3D pre-intervention image.
Multiview 2D/3D Rigid Registration via a Point-Of-Interest Network for Tracking and Triangulation ($\text{POINT}^2$)
As the POI tracker is shift-invariant, $\text{POINT}^2$ is more robust to the initial pose of the 3D pre-intervention image.
Skin Disease Classification versus Skin Lesion Characterization: Achieving Robust Diagnosis using Multi-label Deep Neural Networks
In contrast, for lesion-targeted classification, we can achieve a much higher mAP of 0. 70.
A Deep Multi-task Learning Approach to Skin Lesion Classification
Skin lesion identification is a key step toward dermatological diagnosis.
More Knowledge is Better: Cross-Modality Volume Completion and 3D+2D Segmentation for Intracardiac Echocardiography Contouring
Using catheter ablation to treat atrial fibrillation increasingly relies on intracardiac echocardiography (ICE) for an anatomical delineation of the left atrium and the pulmonary veins that enter the atrium.
Adversarial Sparse-View CBCT Artifact Reduction
We present an effective post-processing method to reduce the artifacts from sparsely reconstructed cone-beam CT (CBCT) images.
Joint Vertebrae Identification and Localization in Spinal CT Images by Combining Short- and Long-Range Contextual Information
For the long-range contextual information, we propose a multi-task bidirectional recurrent neural network (Bi-RNN) to encode the spatial and contextual information among the vertebrae of the visible spine column.
Joint Vertebrae Identification And Localization In Spinal Ct Images
Face Completion with Semantic Knowledge and Collaborative Adversarial Learning
Unlike a conventional background inpainting approach that infers a missing area from image patches similar to the background, face completion requires semantic knowledge about the target object for realistic outputs.
CariGAN: Caricature Generation through Weakly Paired Adversarial Learning
Furthermore, an attention mechanism is introduced to encourage our model to focus on the key facial parts so that more vivid details in these regions can be generated.
Sum of previous inpatient serum creatinine measurements predicts acute kidney injury in rehospitalized patients
Acute Kidney Injury (AKI), the abrupt decline in kidney function due to temporary or permanent injury, is associated with increased mortality, morbidity, length of stay, and hospital cost.
Inferring Restaurant Styles by Mining Crowd Sourced Photos from User-Review Websites
The multi-label CNN is then used to compute the confidence scores of restaurant styles for all the images associated with a restaurant.
Do They All Look the Same? Deciphering Chinese, Japanese and Koreans by Fine-Grained Deep Learning
We find that Chinese, Japanese and Koreans do exhibit substantial differences in certain attributes, such as bangs, smiling, and bushy eyebrows.
