Evaluation of algorithmic requirements for clinical application of material decomposition using a multi-layer flat panel detector [0.03%]
基于多层平板探测器的材料分解算法需求评估
Jamin Schaefer,Steffen Kappler,Ferdinand Lueck et al.
Jamin Schaefer et al.
Purpose: The combination of multi-layer flat panel detector (FPDT) X-ray imaging and physics-based material decomposition algorithms allows for the removal of anatomical structures. However, the reliability of these algor...
Bennett A Landman
Bennett A Landman
The editorial discusses current JMI special sections/issues and calls for papers. © 2025 Society of Photo-Optical Instrumentation Engineers (SPIE).
Assessing mammographic density change within individuals across screening rounds using deep learning-based software [0.03%]
基于深度学习的软件在乳腺癌筛查周期内评估个体乳房密度变化中的应用
Jakob Olinder,Daniel Förnvik,Victor Dahlblom et al.
Jakob Olinder et al.
Purpose: The purposes are to evaluate the change in mammographic density within individuals across screening rounds using automatic density software, to evaluate whether a change in breast density is associated with a fut...
Physician-guided deep learning model for assessing thymic epithelial tumor volume [0.03%]
基于医师指导的评估胸腺上皮肿瘤体积的深度学习模型
Nirmal Choradia,Nathan Lay,Alex Chen et al.
Nirmal Choradia et al.
Purpose: The Response Evaluation Criteria in Solid Tumors (RECIST) relies solely on one-dimensional measurements to evaluate tumor response to treatments. However, thymic epithelial tumors (TETs), which frequently metasta...
ZeroReg3D: a zero-shot registration pipeline for 3D consecutive histopathology image reconstruction [0.03%]
零样本三维连续组织病理图像重建注册框架 ZeroReg3D
Juming Xiong,Ruining Deng,Jialin Yue et al.
Juming Xiong et al.
Purpose: Histological analysis plays a crucial role in understanding tissue structure and pathology. Although recent advancements in registration methods have improved 2D histological analysis, they often struggle to pres...
GRN+: a simplified generative reinforcement network for tissue layer analysis in 3D ultrasound images for chronic low-back pain [0.03%]
用于慢性下背痛的3D超声图像组织层分析的简化生成增强网络（GRN+）
Zixue Zeng,Xiaoyan Zhao,Matthew Cartier et al.
Zixue Zeng et al.
Purpose: 3D ultrasound delivers high-resolution, real-time images of soft tissues, which are essential for pain research. However, manually distinguishing various tissues for quantitative analysis is labor-intensive. We a...
Glo-In-One-v2: holistic identification of glomerular cells, tissues, and lesions in human and mouse histopathology [0.03%]
全局一体化v2（Glo-In-One-v2）：人和小鼠肾组织病理图像中肾球细胞、组织及病灶的端到端联合检测与识别模型
Lining Yu,Mengmeng Yin,Ruining Deng et al.
Lining Yu et al.
Purpose: Segmenting intraglomerular tissue and glomerular lesions traditionally depends on detailed morphological evaluations by expert nephropathologists, a labor-intensive process susceptible to interobserver variabilit...
Deep-learning-based washout classification for decision support in contrast-enhanced ultrasound examinations of the liver [0.03%]
基于深度学习的肝胆超声检查去氧鉴别诊断辅助技术研究
Hannah Strohm,Sven Rothlübbers,Jürgen Jenne et al.
Hannah Strohm et al.
Purpose: Contrast-enhanced ultrasound (CEUS) is a reliable tool to diagnose focal liver lesions, which appear ambiguous in normal B-mode ultrasound. However, interpretation of the dynamic contrast sequences can be challen...
Wavelet-based compression method for scale-preserving in VNIR and SWIR hyperspectral data [0.03%]
基于小波变换的VNIR和SWIR高光谱数据尺度保持压缩方法
Hridoy Biswas,Rui Tang,Shamim Mollah et al.
Hridoy Biswas et al.
Purpose: Hyperspectral imaging (HSI) collects detailed spectral information across hundreds of narrow bands, providing valuable datasets for applications such as medical diagnostics. However, the large size of HSI dataset...
MAFL-Attack: a targeted attack method against deep learning-based medical image segmentation models [0.03%]
针对基于深度学习的医学图像分割模型的 targeted 攻击方法 MAFL-Attack
Junmei Sun,Xin Zhang,Xiumei Li et al.
Junmei Sun et al.
Purpose: Medical image segmentation based on deep learning has played a crucial role in computer-aided medical diagnosis. However, they are still vulnerable to imperceptible adversarial attacks, which lead to potential mi...