Research map: BoostCNN: Deep Learning AdaBoost-based Method for Easy and Difficult Nodule Classification in Ultrasound Images

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  1. A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting · Yoav Freund · 1997 · 20715 citations · Cited by this paper
  2. A Coarse-to-Fine DoubleUNet Framework with Synergistic Loss for Accurate Fetal Head Circumference Measurement · 2026 · Related
  3. Dataset of breast ultrasound images · Walid Al-Dhabyani · 2019 · 2352 citations · Cited by this paper
  4. Ultrasound Shear-wave Elastography Reveals Biomechanical Heterogeneity Following Acute Spinal Cord Injury · 2026 · Related
  5. AdaBoost-CNN: An adaptive boosting algorithm for convolutional neural networks to classify multi-class imbalanced datasets using transfer learning · Aboozar Taherkhani · 2020 · 283 citations · Cited by this paper
  6. Editorial Advisory Board · 2026 · Related
  7. Automatic 3D pulmonary nodule detection in CT images: A survey · Igor R. S. Valente · 2015 · 238 citations · Cited by this paper
  8. Lymphatic and Vascular Dual-System Super-Resolution Ultrasound for Diagnosing Sentinel Lymph Node Metastasis in Breast Cancer: A Prospective Study · 2026 · Related
  9. BUS‐BRA: A breast ultrasound dataset for assessing computer‐aided diagnosis systems · Wilfrido Gómez‐Flores · 2023 · 153 citations · Cited by this paper
  10. Temporal Changes in Shear Wave Elastography and Doppler Ultrasound Parameters for Assessing Erectile Dysfunction · 2026 · Related
  11. Deep Learning in Breast Cancer Imaging: A Decade of Progress and Future Directions · Luyang Luo · 2024 · 151 citations · Cited by this paper
  12. Value of Testicular Shear Wave Dispersion Imaging in Predicting Semen Improvement After Varicocelectomy · 2026 · Related
  13. USFM: A universal ultrasound foundation model generalized to tasks and organs towards label efficient image analysis · Jing Jiao · 2024 · 112 citations · Cited by this paper
  14. A Multimodal Multitask Deep Learning Model Based on Ultrasound RF Signals for Joint Assessment of Breast Masses and Axillary Lymph Nodes Status · 2026 · Related
  15. Curated benchmark dataset for ultrasound based breast lesion analysis · Anna Pawłowska · 2024 · 110 citations · Cited by this paper
  16. Evaluation of the Efficacy of Combined Treatment of Liver Cancer With Losartan and Ultrasound‑Stimulated Microbubble Cavitation · 2026 · Related
  17. Evaluation of Adjunctive Ultrasonography for Breast Cancer Detection Among Women Aged 40-49 Years With Varying Breast Density Undergoing Screening Mammography · Narumi Harada‐Shoji · 2021 · 105 citations · Cited by this paper
  18. A Synthetic Data-Augmented Deep Learning Framework for Robust Segmentation and Quantification of the Carotid Artery in Ultrasound Images · 2026 · Related
  19. Ultrasound for Breast Cancer Screening in Resource-Limited Settings: Current Practice and Future Directions · Qing Dan · 2023 · 58 citations · Cited by this paper
  20. Dynamic Aware Biopsy Needle Identification in Ultrasound Images Using Temporal Prior Guided U-Net Cross Transformer With Limited Training Data · 2026 · Related
  21. Breast cancer screening: review of benefits and harms, and recommendations for developing and low-income countries · Meteb Al‐Foheidi · 2013 · 57 citations · Cited by this paper
  22. GREnet: Gradually REcurrent Network With Curriculum Learning for 2-D Medical Image Segmentation · Jinting Wang · 2023 · 47 citations · Cited by this paper
  23. EH-former: Regional easy-hard-aware transformer for breast lesion segmentation in ultrasound images · Xiaolei Qu · 2024 · 46 citations · Cited by this paper
  24. A computer-aided diagnosis system for breast ultrasound based on weighted BI-RADS classes · Arturo Rodríguez-Cristerna · 2017 · 39 citations · Cited by this paper
  25. Breast cancer screening: emerging role of new imaging techniques as adjuncts to mammography · Nehmat Houssami · 2009 · 37 citations · Cited by this paper
  26. Distribuição espacial de equipamentos de mamografia no Brasil | Spatial distribution of mammography equipment in Brazil · Pedro Amaral · 2017 · 29 citations · Cited by this paper
  27. Improving breast cancer classification in fine-grain ultrasound images through feature discrimination and a transfer learning approach · Fatemeh Taheri · 2025 · 22 citations · Cited by this paper
  28. Letter to the Editor. Re: “[Dataset of breast ultrasound images by W. Al-Dhabyani, M. Gomaa, H. Khaled & A. Fahmy, Data in Brief, 2020, 28, 104863]” · Anna Pawłowska · 2023 · 19 citations · Cited by this paper
  29. Paced-curriculum distillation with prediction and label uncertainty for image segmentation · Mobarakol Islam · 2023 · 10 citations · Cited by this paper
  30. Transfer Learning and Handcrafted Features Ensembles for Ultrasound Breast Cancer Image Classification · Vanessa Kaplum Foleis · 2025 · 8 citations · Cited by this paper
  31. NMTNet: A Multi-task Deep Learning Network for Joint Segmentation and Classification of Breast Tumors · Xuelian Yang · 2025 · 5 citations · Cited by this paper
  32. Multiparametric Ultrasound Breast Tumors Diagnosis Within BI-RADS Category 4 via Feature Disentanglement and Cross-Fusion · Zhikai Ruan · 2025 · 5 citations · Cited by this paper
  33. BD-StableNet: a deep stable learning model with an automatic lesion area detection function for predicting malignancy in BI-RADS category 3–4A lesions · Hui Yan Qu · 2024 · 4 citations · Cited by this paper
  34. Avaliação da Cobertura do Exame Mamográfico de Rastreio do SUS e Mortalidade por Câncer de Mama no Nordeste Brasileiro · Luis Victor Moraes de Moura · 2020 · 2 citations · Cited by this paper
  35. Visual Prompting and Adaptation of Vision Language Models for Tumor Classification in Breast Ultrasound · Ashirbani Saha · 2025 · 2 citations · Cited by this paper

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