{"total":24,"rows":[{"id":"2105.13381","title":"Recent advances and clinical applications of deep learning in medical image analysis","created":"2021-05-27","cited_by_count":104,"area":null},{"id":"2203.07373","title":"SATr: Slice Attention with Transformer for Universal Lesion Detection","created":"2022-03-13","cited_by_count":17,"area":null},{"id":"2109.08684","title":"Asymmetric 3D Context Fusion for Universal Lesion Detection","created":"2021-09-17","cited_by_count":14,"area":null},{"id":"2111.04886","title":"Universal Lesion Detection in CT Scans using Neural Network Ensembles","created":"2021-11-09","cited_by_count":8,"area":null},{"id":"2103.12277","title":"Conditional Training with Bounding Map for Universal Lesion Detection","created":"2021-03-23","cited_by_count":5,"area":null},{"id":"2107.08715","title":"RECIST-Net: Lesion detection via grouping keypoints on RECIST-based annotation","created":"2021-07-19","cited_by_count":4,"area":null},{"id":"2201.01426","title":"Advancing 3D Medical Image Analysis with Variable Dimension Transform based Supervised 3D Pre-training","created":"2022-01-05","cited_by_count":3,"area":null},{"id":"2205.13835","title":"Deep Learning Fetal Ultrasound Video Model Match Human Observers in Biometric Measurements","created":"2022-05-27","cited_by_count":3,"area":null},{"id":"2404.03819","title":"Effective Lymph Nodes Detection in CT Scans Using Location Debiased Query Selection and Contrastive Query Representation in Transformer","created":"2024-04-04","cited_by_count":3,"area":null},{"id":"2103.12972","title":"Hetero-Modal Learning and Expansive Consistency Constraints for Semi-Supervised Detection from Multi-Sequence Data","created":"2021-03-24","cited_by_count":1,"area":null},{"id":"2110.13036","title":"Dual Skip Connections Minimize the False Positive Rate of Lung Nodule Detection in CT images","created":"2021-10-25","cited_by_count":1,"area":null},{"id":"2203.06886","title":"DKMA-ULD: Domain Knowledge augmented Multi-head Attention based Robust Universal Lesion Detection","created":"2022-03-14","cited_by_count":1,"area":null},{"id":"2303.15024","title":"An End-to-End Framework For Universal Lesion Detection With Missing Annotations","created":"2023-03-27","cited_by_count":1,"area":null},{"id":"2309.13306","title":"Tackling the Incomplete Annotation Issue in Universal Lesion Detection Task By Exploratory Training","created":"2023-09-23","cited_by_count":1,"area":null},{"id":"2203.16074","title":"An Efficient Anchor-free Universal Lesion Detection in CT-scans","created":"2022-03-30","cited_by_count":0,"area":null},{"id":"2301.03202","title":"Integrating features from lymph node stations for metastatic lymph node detection","created":"2023-01-09","cited_by_count":0,"area":null},{"id":"2302.04677","title":"Mixed-order self-paced curriculum learning for universal lesion detection","created":"2023-02-09","cited_by_count":0,"area":null},{"id":"2305.16649","title":"FSD: Fully-Specialized Detector via Neural Architecture Search","created":"2023-05-26","cited_by_count":0,"area":null},{"id":"2504.05201","title":"3D Universal Lesion Detection and Tagging in CT with Self-Training","created":"2025-04-07","cited_by_count":0,"area":null},{"id":"2504.05207","title":"Correcting Class Imbalances with Self-Training for Improved Universal Lesion Detection and Tagging","created":"2025-04-07","cited_by_count":0,"area":null},{"id":"2505.18741","title":"MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images","created":"2025-05-24","cited_by_count":0,"area":null},{"id":"2506.03608","title":"PDSE: A Multiple Lesion Detector for CT Images using PANet and Deformable Squeeze-and-Excitation Block","created":"2025-06-04","cited_by_count":0,"area":null},{"id":"2604.24999","title":"BifDet: A 3D Bifurcation Detection Dataset for Airway-Tree Modeling","created":"2026-04-27","cited_by_count":0,"area":null},{"id":"2608.05100","title":"Lesion Detection in CT with Frozen Self-Distilled Features: SALT, a Spatially Adaptive Label-Guided Temperature","created":"2026-08-05","cited_by_count":0,"area":null}],"next_cursor":null}