19 papers · ranked by Valyu relevance
Oshane O. Thomas, A. Murat Maga
Geometric morphometrics is widely employed across the biological sciences for the quantification of morphological traits. However, the scalability of these methods to large datasets is hampered by the requisite placement of landmarks, which can be laborious and time consuming if done manually. Additionally, the…
Claudia Lindner, Ching-Wei Wang, Cheng-Ta Huang, Chung-Hsing Li + 2 more
'Sheng-Wei Chang' 'Tim F. Cootes'] Cephalometric tracing is a standard analysis tool for orthodontic diagnosis and treatment planning. The aim of this study was to develop and validate a fully automatic landmark annotation (FALA) system for finding cephalometric landmarks in lateral cephalograms and its application to…
You Wu, Jing Zhai, Yufei Wang, Yawen Zhang + 4 more
Objectives This study aimed to conduct a scoping review to systematically review automatic identification techniques for soft-tissue and hard-tissue landmarks in three-dimensional (3D)-computed tomography (CT)/cone-beam computed tomography (CBCT), particularly focusing on artificial intelligence (AI)-based methods, to…
Babak A. Ardekani
This technical report presents the Automatic Temporal Registration Algorithm (ATRA) for symmetric rigid-body affine registration of longitudinal T_1_-weighted three-dimensional magnetic resonance imaging (MRI) scans of the human brain. This is a fundamental processing step in computational neuroimaging. The notion of…
Julia M. H. Noothout, Bob D. de Vos, Jelmer M. Wolterink, Elbrich M. Postma + 5 more
'Elbrich M. Postma' 'Paul A.M. Smeets' 'Richard A. P. Takx' 'Tim Leiner' 'Max A. Viergever' 'Ivana Išgum'] Abstract—In this study, we propose a fast and accurate method to automatically localize anatomical landmarks in medical images. We employ a global-to-local localization approach using fully convolutional neural…
Julie D. White, Alejandra Ortega-Castrillón, Harold Matthews, Arslan A. Zaidi + 7 more
In the post-genomics era, an emphasis has been placed on disentangling ‘genotype-phenotype’ connections so that the biological basis of complex phenotypes can be understood. However, our ability to efficiently and comprehensively characterize phenotypes lags behind our ability to characterize genomes. Here, we report a…
Srikanth Vasamsetti, Viren Sardana, Prasoon Kumar, H.K Sardana
Manual cephalogram marking has long way from marking on tracing sheet to availability of commercial software's for cephalometric analysis. With the effort involved in manual marking and time consumption, it becomes imperative for modern science to envisage algorithms which could automatically locate landmarks on the…
Zhen Li, Yuliang Gao, Miaomiao Zhu, Haonan Tang + 2 more
'Andrey V. Savkin'] With the development of automation and intelligent technologies, the demand for autonomous mobile robots in the industry has surged to alleviate labor-intensive tasks and mitigate labor shortages. However, conventional industrial mobile robots’ route-tracking algorithms typically rely on passive…
Julia M. H. Noothout, Bob D. de Vos, Jelmer M. Wolterink, Tim Leiner + 1 more
'Ivana Išgum'] Automatic landmark detection is performed with a patch-based fully convolutional neural network (FCNN) that combines regression and classification. For any given image patch, regression is used to predict the 3D displacement vector from the image patch to the landmark. Simultaneously, classification is…
Muhammad Anwaar Khalid, Kanwal Zulfiqar, Ulfat Bashir, Areeba Shaheen + 4 more
'Areeba Shaheen' 'Rida Iqbal' 'Zarnab Rizwan' 'Ghina Rizwan' 'Muhammad Moazam Fraz'] Quantitative cephalometry is the most widely used clinical and research tool in modern orthodontics, enabling the quantification and classification of anatomical abnormalities through localization of cephalometric landmarks. However…
Hwangyu Lee, Jung Min Cho, Susie Ryu, Seungmin Ryu + 3 more
'Young-Soo Jung' 'Jun-Young Kim'] This study aimed to propose a fully automatic posteroanterior (PA) cephalometric landmark identification model using deep learning algorithms and compare its accuracy and reliability with those of expert human examiners. In total, 1032 PA cephalometric images were used for model…
Congyi Zhao, Zengbei Yuan, Shichang Luo, Wenjie Wang + 3 more
'Xufeng Yao' 'Tao Wu'] The identification of head landmarks in cephalometric analysis significantly contributes in the anatomical localization of maxillofacial tissues for orthodontic and orthognathic surgery. However, the existing methods face the limitations of low accuracy and cumbersome identification process. In…
Shumeng Wang, Huiqi Li, Jiazhi Li, Yanjun Zhang + 1 more
Cephalometric analysis is a standard tool for assessment and prediction of craniofacial growth, orthodontic diagnosis, and oral-maxillofacial treatment planning. The aim of this study is to develop a fully automatic system of cephalometric analysis, including cephalometric landmark detection and cephalometric…
Mateo Cámara, José Luis Blanco, Juan Ignacio Godino-Llorente, Jeung-Yoon Choi + 1 more
Acoustic landmark theory treats speech as organized around the acoustic consequences of articulatory gestures that shape the vocal tract and airflow. Progress is limited by the scarcity of large, unambiguously annotated landmark datasets. We invert the problem by generating speech from landmark patterns. Using the Pink…
Brénainn Woodsend, Eirini Koufoudaki, Peter Mossey, Ping Lin
We have developed techniques and software implementing these techniques to map out automatically, 3D dental scans. This process is divided into consecutive steps – determining a model's orientation, separating and identifying the individual tooth and finding landmarks on each tooth – described in this paper. Examples…
Sara Neves Silva, Sarah McElroy, Jordina Aviles Verdera, Kathleen Colford + 10 more
'Kathleen Colford' 'Kamilah St Clair' 'Raphaël Tomi‐Tricot' 'Alena Uus' 'Valéry Ozenne' 'Megan Hall' 'Lisa Story' 'Kuberan Pushparajah' 'Mary Rutherford' 'Joseph V. Hajnal' 'Jana Hutter'] Methods: Deep learning-based detection of key brain landmarks on a whole-uterus EPI scan enables the subsequent fully automatic…
Di He, Boon Pang Lim, Xuesong Yang, Mark Hasegawa‐Johnson + 1 more
'Deming Chen'] Most mainstream Automatic Speech Recognition (ASR) systems consider all feature frames equally important. However, acoustic landmark theory is based on a contradictory idea, that some frames are more important than others. Acoustic landmark theory exploits quantal non-linearities in the…
Ruijia Chen, Junru Jiang, Pragati Maheshwary, Brianna R Cochran + 1 more
Researchers have developed landmark enhancement systems in AR for sighted people. Zhang et al. found that the AR navigation system with landmarks enhanced users' mental map development and improved wayfinding performance. Liu et al. used AR icons to label semantic landmarks, showing that virtual semantic landmarks can…
Riley Hickman, Malcolm Sim, Sergio Pablo-García, Ivan Woolhouse + 6 more
Self-driving laboratories (SDLs) are next-generation research and development platforms for closed-loop, autonomous experimentation that combine ideas from artificial intelligence, robotics, and high-performance computing. A critical component of SDLs is the decision-making algorithm used to prioritize experiments to…