Results 91 to 100 of about 8,805 (204)

COMPUTING THE HAUSDORFF DISTANCE BETWEEN CURVED OBJECTS

International Journal of Computational Geometry & Applications, 2008
The Hausdorff distance between two sets of curves is a measure for the similarity of these objects and therefore an interesting feature in shape recognition. If the curves are algebraic computing the Hausdorff distance involves computing the intersection points of the Voronoi edges of the one set with the curves in the other.
Alt, Helmut, Scharf, Ludmila
openaire   +3 more sources

Advances in 4D Representation: Geometry, Motion, and Interaction

Computer Graphics Forum, EarlyView.
We survey 4D representation through three key pillars — geometry, motion, and interaction — offering a selective, representation‐centric perspective to guide researchers in choosing and customizing the right 4D representation for their tasks. Abstract We present a survey on 4D generation and reconstruction, a fast‐evolving subfield of computer graphics
M. Zhao, S. Nag, K. Wang, A. Vora, G. Ji, P. Chun, A. Mahdavi‐Amiri, H. Zhang   +7 more
wiley   +1 more source

Target Detection Based on Improved Hausdorff Distance Matching Algorithm for Millimeter-Wave Radar and Video Fusion. [PDF]

Sensors (Basel), 2022
Xu D, Liu Y, Wang Q, Wang L, Liu R.
europepmc   +1 more source

Deep Learning for Assessing Caries Depth in Permanent Teeth Using Intraoral Radiographs: A Systematic Review

International Endodontic Journal, EarlyView.
ABSTRACT Background Accurate assessment of caries depth on intraoral radiographs is crucial for determining the extent of the lesion and planning appropriate treatment. Artificial intelligence (AI) models have been increasingly used for detecting and classifying carious lesions; however, the evidence focusing specifically on the classification of ...
Laith Abu Qdais, Richard Gault, Jamie Toole, Aysar Khudair, Omer Butt, Ikhlas El‐Karim   +5 more
wiley   +1 more source

Deep learning assisted high‐resolution microscopy image processing for phase segmentation in functional composite materials

Journal of Microscopy, EarlyView.
Abstract In the domain of battery research, the processing of high‐resolution microscopy images is a challenging task, as it involves dealing with complex images and requires a prior understanding of the components involved. The utilisation of deep learning methodologies for image analysis has attracted considerable interest in recent years, with ...
Ganesh Raghavendran, Bing Han, Fortune Adekogbe, Shuang Bai, Bingyu Lu, William Wu, Minghao Zhang, Ying Shirley Meng   +7 more
wiley   +1 more source

Can Deep Learning Methods Differentiate Temporomandibular Joint Disorders From Healthy Joints? A 3D Artificial Intelligence Algorithm Study Based on CBCT Images

Journal of Oral Rehabilitation, EarlyView.
In this study, an integrated deep learning approach was developed for the evaluation of temporomandibular joint disorders using multicentre CBCT images. The mandibular condyle was first automatically segmented using the nnU‐Net v2 architecture. Subsequently, 3D‐CNN algorithms classified the condyles as healthy or unhealthy and further distinguished ...
İbrahim Şevki Bayrakdar, Sevda Kurt‐Bayrakdar, Alican Kuran, Özer Çelik, Kaan Orhan, Rohan Jagtap   +5 more
wiley   +1 more source

Artificial Intelligence in Orthodontics: Part 2—Data Preparation and Performance Evaluation

Orthodontics &Craniofacial Research, EarlyView.
ABSTRACT Artificial intelligence (AI) is increasingly integrated into orthodontic research and clinical workflows. Yet, the reliability and clinical value of these systems depend fundamentally on the quality of the data used to train them and the rigour with which their performance is evaluated.
Khuram Naveed, Fatemeh Sohrabniya, Hossein Mohammad‐Rahimi, Julian Woolley, Ruben Pauwels, Peter Bangsgaard Stoustrup   +5 more
wiley   +1 more source

The Evolution of Breast Cancer Detection: A Review of Imaging, Machine Learning, and Multimodal Strategies

Computational and Systems Oncology, Volume 6, Issue 1, December 2026.
ABSTRACT Breast cancer is still a serious problem in the world arena, where its early and prompt detection is the most important factor in improving patient prognosis and survival. The use of traditional diagnostic techniques, such as imaging (e.g., mammography and ultrasound) and subsequent histopathological examination, is the mainstay, which ...
Likhon Chandra Sarkar, Farida Siddiqi Prity, Farhad Hussain, Anup Talukder, Mirza Raquib, Sharmina Rahman, MD Jiabul Hoque   +6 more
wiley   +1 more source

Fractional Moment Theory for Anomalous Transport: A Unified Framework for Lévy Flights, Fractals, and Complex Dynamical Systems

Mathematical Methods in the Applied Sciences, Volume 49, Issue 13, Page 14964-15009, 15 September 2026.
ABSTRACT We develop a unified mathematical framework extending classical moment theory from discrete integer orders to a continuous spectrum of real orders f>0$$ f>0 $$, providing a systematic statistical characterization of complex systems exhibiting power‐law behavior.
Farrukh A. Chishtie
wiley   +1 more source

Deep learning auto‐contouring of target and organs‐at‐risk on post‐catheter implant CT images for prostate HDR brachytherapy

Journal of Applied Clinical Medical Physics, Volume 27, Issue 9, September 2026.
Abstract Background Accurate delineation of the prostate and surrounding organs‐at‐risk (OARs) is essential for HDR prostate brachytherapy. Manual contouring on post‐catheter CT images is time‐consuming and prone to variability due to artifacts and anatomical deformation from the implanted brachytherapy catheters.
Eric M. Wallat, Joseph B. Schulz, John M. Floberg, Gregory Cooley, Bryan P. Bednarz, Jordan M. Slagowski   +5 more
wiley   +1 more source