Evaluation of data augmentation via synthetic images for improved breast mass detection on mammograms using deep learning [0.03%]
基于深度学习的乳腺X线影像肿块检测的数据增强方法研究
Kenny H Cha,Nicholas Petrick,Aria Pezeshk et al.
Kenny H Cha et al.
We evaluated whether using synthetic mammograms for training data augmentation may reduce the effects of overfitting and increase the performance of a deep learning algorithm for breast mass detection. Synthetic mammograms were generated us...
Automatic quantification of HER2 gene amplification in invasive breast cancer from chromogenic in situ hybridization whole slide images [0.03%]
基于染色原位杂交技术的乳腺癌HER2基因扩增的定量分析方法研究
Md Shakhawat Hossain,Matthew G Hanna,Naohiro Uraoka et al.
Md Shakhawat Hossain et al.
Human epidermal growth factor receptor 2 (HER2), a transmembrane tyrosine kinase receptor encoded by the ERBB2 gene on chromosome 17q12, is a predictive and prognostic biomarker in invasive breast cancer (BC). Approximately 20% of BC are HE...
Segmentation of retinal blood vessels based on feature-oriented dictionary learning and sparse coding using ensemble classification approach [0.03%]
基于特征导向字典学习和稀疏编码的集合分类方法的视网膜血管分割算法研究
Navdeep Singh,Lakhwinder Kaur,Kuldeep Singh
Navdeep Singh
Accurate segmentation of the blood vessels from a retinal image plays a significant role in the prudent examination of the vessels. A supervised blood vessel segmentation technique to extract blood vessels from a retinal image is proposed. ...
Stochastic tissue window normalization of deep learning on computed tomography [0.03%]
基于CT影像的深度学习随机组织窗标准化方法
Yuankai Huo,Yucheng Tang,Yunqiang Chen et al.
Yuankai Huo et al.
Tissue window filtering has been widely used in deep learning for computed tomography (CT) image analyses to improve training performance (e.g., soft tissue windows for abdominal CT). However, the effectiveness of tissue window normalizatio...
Robust regression-based estimation of isocenter offset with subpixel precision in tomographic image reconstruction [0.03%]
基于稳健回归的层析图像重建亚像素精度等中心偏移估算方法
Xuelin Cui,Lamine Mili,Ibrahim Bechwati et al.
Xuelin Cui et al.
Tomographic image reconstruction requires precise geometric measurements and calibration for the scanning system to yield optimal images. The isocenter offset is a very important geometric parameter that directly governs the spatial resolut...
Regional dynamics of fractal dimension of the left ventricular endocardium from cine computed tomography images [0.03%]
基于断层扫描图像的心室左内膜的分形维数区域动力学分析
Ashish Manohar,Lorenzo Rossini,Gabrielle Colvert et al.
Ashish Manohar et al.
We present a method to leverage the high fidelity of computed tomography (CT) to quantify regional left ventricular function using topography variation of the endocardium as a surrogate measure of strain. 4DCT images of 10 normal and 10 abn...
Tissue classification in intercostal and paravertebral ultrasound using spectral analysis of radiofrequency backscatter [0.03%]
基于射频回波的光谱分析在肋间和脊旁超声组织分类中的应用
Jon D Klingensmith,Asher L Haggard,Jack T Ralston et al.
Jon D Klingensmith et al.
Paravertebral and intercostal nerve blocks have experienced a resurgence in popularity. Ultrasound has become the gold standard for visualization of the needle during injection of the analgesic, but the intercostal artery and vein can be di...
SLICR super-voxel algorithm for fast, robust quantification of myocardial blood flow by dynamic computed tomography myocardial perfusion imaging [0.03%]
动态CT心肌灌注成像的SLICR超体素算法可实现快速、稳健的心肌血流量计算
Hao Wu,Brendan L Eck,Jacob Levi et al.
Hao Wu et al.
We created and evaluated a processing method for dynamic computed tomography myocardial perfusion imaging (CT-MPI) of myocardial blood flow (MBF), which combines a modified simple linear iterative clustering algorithm (SLIC) with robust per...
Heuristic neural network approach in histological sections detection of hydatidiform mole [0.03%]
奇胎病理切片的启发式神经网络方法
Patison Palee,Bernadette Sharp,Leonard Noriega et al.
Patison Palee et al.
A heuristic-based, multineural network (MNN) image analysis as a solution to the problematical diagnosis of hydatidiform mole (HM) is presented. HM presents as tumors in placental cell structures, many of which exhibit premalignant phenotyp...
Deep learning-based image quality improvement for low-dose computed tomography simulation in radiation therapy [0.03%]
基于深度学习的低剂量放疗CT模拟图像质量改善方法研究
Tonghe Wang,Yang Lei,Zhen Tian et al.
Tonghe Wang et al.
Low-dose computed tomography (CT) is desirable for treatment planning and simulation in radiation therapy. Multiple rescanning and replanning during the treatment course with a smaller amount of dose than a single conventional full-dose CT ...