9 Result(s)
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Article
Open AccessUsing GPT-4 to write a scientific review article: a pilot evaluation study
GPT-4, as the most advanced version of OpenAI’s large language models, has attracted widespread attention, rapidly becoming an indispensable AI tool across various areas. This includes its exploration by scien...
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Chapter and Conference Paper
CA-Net: Leveraging Contextual Features for Lung Cancer Prediction
In the early diagnosis of lung cancer, an important step is classifying malignancy/benignity for each lung nodule. For this classification, the nodule’s features (e.g., shape, margin) have traditionally been t...
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Chapter and Conference Paper
DAE-GCN: Identifying Disease-Related Features for Disease Prediction
Learning disease-related representations plays a critical role in image-based cancer diagnosis, due to its trustworthy, interpretable and good generalization power. A good representation should not only be dis...
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Chapter and Conference Paper
Symmetry-Enhanced Attention Network for Acute Ischemic Infarct Segmentation with Non-contrast CT Images
Quantitative estimation of the acute ischemic infarct is crucial to improve neurological outcomes of the patients with stroke symptoms. Since the density of lesions is subtle and can be confounded by normal ph...
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Chapter and Conference Paper
Multi-stream Progressive Up-Sampling Network for Dense CT Image Reconstruction
Pulmonary computerized tomography (CT) images with small slice thickness (thin) is very helpful in clinical practice due to its high resolution for precise diagnosis. However, there are still a lot of CT image...
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Chapter and Conference Paper
Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT Slices
Universal lesion detection from computed tomography (CT) slices is important for comprehensive disease screening. Since each lesion can locate in multiple adjacent slices, 3D context modeling is of great signi...
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Chapter and Conference Paper
Towards Robust Bone Age Assessment: Rethinking Label Noise and Ambiguity
The effects of label noise and ambiguity are widespread, especially for subjective tasks such as bone age assessment (BAA). However, most existing BAA algorithms ignore these issues. We propose a robust framew...
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Chapter and Conference Paper
BR-GAN: Bilateral Residual Generating Adversarial Network for Mammogram Classification
Mammogram malignancy classification with only image-level annotations is challenging due to a lack of lesion annotations. If we can generate the healthy version of the diseased data, we can easily explore the ...
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Chapter and Conference Paper
Unsupervised Surgical Instrument Segmentation via Anchor Generation and Semantic Diffusion
Surgical instrument segmentation is a key component in develo** context-aware operating rooms. Existing works on this task heavily rely on the supervision of a large amount of labeled data, which involve lab...
