Enhancing deep learning interpretability for hand-crafted feature-guided histologic image classification via weak-to-strong generalization [0.03%]
通过弱到强的泛化增强手工艺品特征引导的组织学图像分类的深度学习解释性
Zong Fan,Changjie Lu,Jialin Yue et al.
Zong Fan et al.
Purpose: Deep learning (DL) models have achieved promising performance in histologic whole-slide image analysis for various clinical applications. However, their black-box nature hinders the interpretability of DL feature...
Efficient computed tomography-based image segmentation for predicting lateral cervical lymph node metastasis in papillary thyroid carcinoma [0.03%]
基于高效CT图像分割的预测乳头状甲状腺癌侧颈淋巴结转移的方法
Lei Xu,Bin Zhang,Xingyuan Li et al.
Lei Xu et al.
Purpose: Papillary thyroid carcinoma (PTC) is a common thyroid cancer, and accurate preoperative assessment of lateral cervical lymph node metastasis is critical for surgical planning. Current methods are often subjective...
Radiomic signatures from baseline CT predict chemotherapy response in unresectable colorectal liver metastases [0.03%]
基线CT的影像组学特征可预测不可切除结直肠癌肝转移患者的化疗疗效
Mane Piliposyan,Jacob J Peoples,Mohammad Hamghalam et al.
Mane Piliposyan et al.
Purpose: Colorectal cancer is the third most common cancer globally, with a high mortality rate due to metastatic progression, particularly in the liver. Surgical resection remains the main curative treatment, but only a ...
BAF-UNet: a boundary-aware segmentation model for skin lesion segmentation [0.03%]
一种边界感知的皮肤病变分割模型BAF-UNet
Menglei Zhang,Congwei Zhang,Zhibin Quan et al.
Menglei Zhang et al.
Purpose: Skin lesion segmentation plays a significant role in the diagnosis and treatment of skin cancer. Accurate skin lesion segmentation is essential for skin cancer diagnosis and treatment but is challenged by ambiguo...
Characterizing the effects of noncontrast head CT reconstruction kernel and slice thickness parameters on the performance of an automated AI algorithm in the evaluation of ischemic stroke [0.03%]
描述非增强头部CT重建核函数和层厚参数对评估缺血性卒中的自动化AI算法性能的影响
Spencer H Welland,Grace Hyun J Kim,Anil Yadav et al.
Spencer H Welland et al.
Purpose: There are multiple commercially available, Food and Drug Administration (FDA)-cleared, artificial intelligence (AI)-based tools automating stroke evaluation in noncontrast computed tomography (NCCT). This study a...
LiteMIL: a computationally efficient cross-attention multiple instance learning for cancer subtyping on whole-slide images [0.03%]
LiteMIL：一种用于整个切片图像上癌症亚型分类的计算高效交叉注意力多重实例学习方法
Haitham Kussaibi
Haitham Kussaibi
Purpose: Accurate cancer subtyping is essential for precision medicine but challenged by the computational demands of gigapixel whole-slide images (WSIs). Although transformer-based multiple instance learning (MIL) method...
Synthetic multi-inversion time magnetic resonance images for visualization of subcortical structures [0.03%]
用于皮质下结构可视化的合成多反转时间磁共振图像
Savannah P Hays,Lianrui Zuo,Anqi Feng et al.
Savannah P Hays et al.
Purpose: Visualization of subcortical gray matter is essential in neuroscience and clinical practice, particularly for disease understanding and surgical planning. Although multi-inversion time (multi-TI) T 1 -weighted...
LCSD-Net: a light-weight cross-attention-based semantic dual transformer for domain generalization in melanoma detection [0.03%]
LCSD-Net:一种轻量级交叉注意力的语义双Transformer用于黑色素瘤检测的领域泛化
Rishi Agrawal,Neeraj Gupta,Anand Singh Jalal
Rishi Agrawal
Purpose: Research in deep learning has shown a great advancement in the detection of melanoma. However, recent literature has emphasized a tendency of certain models to rely on disease-irrelevant visual artifacts such as ...
Attention-driven framework to segment renal ablation zone in posttreatment CT images: a step toward ablation margin evaluation [0.03%]
一种基于注意力驱动的肾消融区域分割框架：迈向消融边界评估的第一步
Maryam Rastegarpoor,Derek W Cool,Aaron Fenster
Maryam Rastegarpoor
Purpose: Thermal ablation is a minimally invasive therapy used for the treatment of small renal cell carcinoma tumors. Treatment success is evaluated on postablation computed tomography (CT) to determine if the ablation z...
Hasan Md Tusfiqur Alam,Tim Maurer,Abdulrahman Mohamed Selim et al.
Hasan Md Tusfiqur Alam et al.
Purpose: Centralized machine learning often struggles with limited data access and expert involvement. We investigate decentralized approaches that preserve data privacy while enabling collaborative model training for med...