Description
Book Synopsis.- A Lightweight Optimization Framework for Estimating 3D Brain Tumor Infiltration.
.- A Data-Driven Approach to Optimise Parameters of a Computational Digital Twin Model in Response to SBRT on MR-Linac.
.- FMIC-AI: Annotation-Free Tumor Cell Detection in Fluorescence Microscopy via Self-Supervised Anomaly Detection.
.- Score-based Diffusion Model for Unpaired Virtual Histology Staining.
.- Redefining Spectral Unmixing for In-Vivo BrainTissue Analysis from Hyperspectral Imaging.
.- CT Image Segmentation Using Frequency Domain Feature-Assisted Selective Long Memory State Space Model.
.- Towards Robust Skin Lesion Classification: Lesion Segmentation, Mole Collision Simulation and Hierarchical learning.
.- Key Clinical Parameters Detection and Ovarian Tumor Benign/Malignant Classification in Multi-Modal Ultrasound Images via a Multi-Task Model.
.- OG-SAM: Enhancing Multi-Organ Segmentation with Organogenesis-Based Adaptive Modeling.
.- CoMoSeg: Anatomical Consistency and Cross Modality Guidance for Robust Brain Tumor Segmentation Using Partially Labeled MR Sequences.
.- Region-aware Diagnosis of Clinically Significant Prostate Cancer via Semi-supervised Learning Segmentation.
.- GraphMMP: A Graph Neural Network Model with Mutual Information and Global Fusion for Multimodal Medical Prognosis.
.- Dual-Guided 3D Liver CT Image Generation for Medical Analysis.
.- HaDM-ST: Histology-Assisted Differential Modeling for Spatial Transcriptomics Generation.
.- Projection-Driven Robust Motion Compensation for CBCT Using a Patient-Specific Model Learned from Prior Scans.
.- Revealing New Possibilities for Breast MRI Enhancement: Mamba-Driven Cross-Attention GAN with VMKANet.
.- Hierarchical Brain Structure Modeling for Predicting Genotype of Glioma.
