Surgical applications of the Ultraleap 3Di-based gesture-controlled 3D imaging visualization system [0.03%]
基于Ultraleap 3Di的手势控制三维影像视觉系统的手术应用
Zhengnan Liu,Bin Wang,Jixing Lin et al.
Zhengnan Liu et al.
Consequently, accurate visual information and flexible image retrieval are critical to ensure surgical safety and efficiency.
Artificial intelligence assistance using deep metric learning vs. object detection in classifying lumbar disc degeneration on magnetic resonance images [0.03%]
基于深度度量学习与目标检测的人工智能技术在磁共振影像腰椎间盘突出症分类中的应用研究
N Pongsakonpruttikul,C Angthong,V Kittichai et al.
N Pongsakonpruttikul et al.
OBJECTIVE: This study aimed to assess the performance of an image retrieval system based on the deep metric learning (DML) approach in discriminating between early and late stages of degenerative intervertebral disc degeneration (IDD).
Revisit Weakly Supervised Hashing with Deep Multi-modal Foundation Models [0.03%]
基于深度多模态基础模型的弱监督哈希研究
Min Wang,Wengang Zhou,Houqiang Li
Min Wang
In a real-world image retrieval system, images are collected together with user-annotated tags from the web. These tags contain various information about the corresponding image and could be used as weak supervision for image representation learning.
Deep hashing for global registration of preoperative CT and video images for laparoscopic liver surgery [0.03%]
术前CT和腹腔镜肝手术视频图像的全局配准的深度哈希算法研究
Hanyuan Zhang,Sandun Bulathsinhala,Brian R Davidson et al.
Hanyuan Zhang et al.
Methods: We propose the use of a content-based image retrieval (CBIR) framework to obtain an automatic robust initialisation to the registration.
Influence of content-based image retrieval on the accuracy and inter-reader agreement of usual interstitial pneumonia CT pattern classification [0.03%]
基于内容的图像检索对寻常间质性肺炎CT模式分类的准确性及阅片人之间一致性的影响研究
Sohee Park,Hye Jeon Hwang,Jihye Yun et al.
Sohee Park et al.
Objectives: To investigate whether a content-based image retrieval (CBIR) of similar chest CT images can help usual interstitial pneumonia (UIP) CT pattern classifications among readers with varying levels of experience.
Improving neck ultrasound image retrieval using intra-sweep representation learning [0.03%]
基于回扫表示学习的颈部超声图像检索方法研究
Wanwen Chen,Adam Schmidt,Eitan Prisman et al.
Wanwen Chen et al.
We also demonstrate the feasibility of using our image retrieval method to provide neck US localization on real patients US after tongue retraction. Total number of words: 2414 words.
Preclinical Evaluation of an Interactive Image Search System of Oral Pathology [0.03%]
口腔病理图像互动检索系统的临床前评价研究
R R Herdiantoputri,D Komura,M Ochi et al.
R R Herdiantoputri et al.
An image search or content-based image retrieval (CBIR) system may help diagnose rare tumors by providing histologically similar reference images, thus reducing the pathologists' workload.
[Cross modal medical image online hash retrieval based on online semantic similarity] [0.03%]
基于在线语义相似度的跨模态医疗图像在线哈希检索方法
Qinghai Liu,Lun Tang,Qianlin Wu et al.
Qinghai Liu et al.
Online hashing methods are receiving increasing attention in cross modal medical image retrieval research. However, existing online methods often lack the learning ability to maintain semantic correlation between new and existing data.
Seeing through multimode fibers using real-valued intensity transmission matrix with deep learning [0.03%]
基于深度学习的实数强度传输矩阵多模光纤成像研究
Ziyu Ye,Tianrui Zhao,Wenfeng Xia
Ziyu Ye
In this work, we propose a hybrid approach that combines a real-valued intensity transmission matrix (RVITM) with deep learning for enhanced image retrieval through MMFs.
Alessio Cece,Massimo Agresti,Nadia De Falco et al.
Alessio Cece et al.
Notable advancements include content-based image retrieval (CBIR), enhanced saliency CBIR (SE-CBIR), Restore-Generative Adversarial Networks (GANs), and Vision Transformers (ViTs).
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