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Found 9 papers, 3 papers with code
Correlation-Aware Mutual Learning for Semi-supervised Medical Image Segmentation
Our approach is based on a mutual learning strategy that incorporates two modules: the Cross-sample Mutual Attention Module (CMA) and the Omni-Correlation Consistency Module (OCC).
Advancing 3D Medical Image Analysis with Variable Dimension Transform based Supervised 3D Pre-training
The difficulties in both data acquisition and annotation substantially restrict the sample sizes of training datasets for 3D medical imaging applications.
Ranked #1 on
Medical Object Detection
on DeepLesion
Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT Slices
We demonstrate that with the novel pre-training method, the proposed MP3D FPN achieves state-of-the-art detection performance on the DeepLesion dataset (3. 48% absolute improvement in the sensitivity of FPs@0. 5), significantly surpassing the baseline method by up to 6. 06% (in MAP@0. 5) which adopts 2D convolution for 3D context modeling.
Ranked #4 on
Medical Object Detection
on DeepLesion
Invasiveness Prediction of Pulmonary Adenocarcinomas Using Deep Feature Fusion Networks
In this study, we explore the fusion of the two kinds of features and claim that radiomics features can be complementary to deep-learning features.
Automatic Calcium Scoring in Cardiac and Chest CT Using DenseRAUnet
We prove the robustness and generalizability of our model by training it exclusively on chest CT while test on both types of CT scans.
Delving Deep into Liver Focal Lesion Detection: A Preliminary Study
Hepatocellular carcinoma (HCC) is the second most frequent cause of malignancy-related death and is one of the diseases with the highest incidence in the world.
Cross-view Relation Networks for Mammogram Mass Detection
Mammogram is the most effective imaging modality for the mass lesion detection of breast cancer at the early stage.
Towards Photo-Realistic Visible Watermark Removal with Conditional Generative Adversarial Networks
Visible watermark plays an important role in image copyright protection and the robustness of a visible watermark to an attack is shown to be essential.
Group-Attention Single-Shot Detector (GA-SSD): Finding Pulmonary Nodules in Large-Scale CT Images
In this paper, we propose a novel and effective abnormality detector implementing the attention mechanism and group convolution on 3D single-shot detector (SSD) called group-attention SSD (GA-SSD).
Computed Tomography (CT)
Finding Pulmonary Nodules In Large-Scale Ct Images
