2 citations · 4 across the 12 of their papers we have counts for
12 papers
Ordinal Learning: Longitudinal Attention Alignment Model for Predicting Time to Future Breast Cancer Events from Mammograms
Xin Wang, Tao Tan, Yuan Gao +9
Precision breast cancer (BC) risk assessment is crucial for developing individualized screening and prevention. Despite the promising potential of recent mammogram (MG) based deep…
Non-Adversarial Learning: Vector-Quantized Common Latent Space for Multi-Sequence MRI
Luyi Han, Tao Tan, Tianyu Zhang +7
Adversarial learning helps generative models translate MRI from source to target sequence when lacking paired samples. However, implementing MRI synthesis with adversarial learning…
To deform or not: treatment-aware longitudinal registration for breast DCE-MRI during neoadjuvant chemotherapy via unsupervised keypoints detection
Luyi Han, Tao Tan, Tianyu Zhang +7
Clinicians compare breast DCE-MRI after neoadjuvant chemotherapy (NAC) with pre-treatment scans to evaluate the response to NAC. Clinical evidence supports that accurate longitudin…
DisAsymNet: Disentanglement of Asymmetrical Abnormality on Bilateral Mammograms using Self-adversarial Learning
Xin Wang, Tao Tan, Yuan Gao +6
Asymmetry is a crucial characteristic of bilateral mammograms (Bi-MG) when abnormalities are developing. It is widely utilized by radiologists for diagnosis. The question of 'what…
Synthesis of Contrast-Enhanced Breast MRI Using Multi-b-Value DWI-based Hierarchical Fusion Network with Attention Mechanism
Tianyu Zhang, Luyi Han, Anna D'Angelo +7
Magnetic resonance imaging (MRI) is the most sensitive technique for breast cancer detection among current clinical imaging modalities. Contrast-enhanced MRI (CE-MRI) provides supe…
An Explainable Deep Framework: Towards Task-Specific Fusion for Multi-to-One MRI Synthesis
Luyi Han, Tianyu Zhang, Yunzhi Huang +6
Multi-sequence MRI is valuable in clinical settings for reliable diagnosis and treatment prognosis, but some sequences may be unusable or missing for various reasons. To address th…
IMPORTANT-Net: Integrated MRI Multi-Parameter Reinforcement Fusion Generator with Attention Network for Synthesizing Absent Data
Tianyu Zhang, Tao Tan, Luyi Han +5
Magnetic resonance imaging (MRI) is highly sensitive for lesion detection in the breasts. Sequences obtained with different settings can capture the specific characteristics of les…
Synthesis-based Imaging-Differentiation Representation Learning for Multi-Sequence 3D/4D MRI
Luyi Han, Tao Tan, Tianyu Zhang +5
Multi-sequence MRIs can be necessary for reliable diagnosis in clinical practice due to the complimentary information within sequences. However, redundant information exists across…
Hermite-Gaussian-mode coherently composed states and deep learning based free-space optical communication link
Zilong Zhang, Suyi Zhao, Wei He +6
In laser-based free-space optical communication, besides OAM beams, Hermite-Gaussian (HG) modes or HG-mode coherently composed states (HG-MCCS) can also be adopted as the informati…
Self-healing and transformation characteristics of obstructed Hermite-Gaussian modes composed structured beams
Suyi Zhao, Zilong Zhang, Yuan Gao +3
The self-healing property of laser beams is of great interest. And a laser beam with spatial structures is also widely concerned due to its important applications in lots of areas.…
Transverse mode selective laser with gain regulation by a digital micromirror device
Zilong Zhang, Yuan Gao, Xin Wang +3
A transverse mode selective laser system with gain regulation by a digital micromirror device (DMD) is presented in this letter. The gain regulation in laser medium is adjusted by…
Generation of Chinese-characters-like modes with transverse mode locked lasers
Zilong Zhang, Yuan Gao, Changming Zhao
Spontaneous transverse mode locking to generate optical vortex arrays is already widely studied for the frequency degenerated transverse modes. While, the mode locking between tran…