4.6 Article

Deep Segmentation of the Mandibular Canal: A New 3D Annotated Dataset of CBCT Volumes

Related references

Note: Only part of the references are listed.
Article Dentistry, Oral Surgery & Medicine

Development and validation of a novel artificial intelligence driven tool for accurate mandibular canal segmentation on CBCT

Pierre Lahoud et al.

Summary: This study developed and validated a novel AI-driven tool for fast and accurate mandibular canal segmentation on CBCT scans. Using a deep learning algorithm trained on 235 CBCT scans, the automated segmentation demonstrated high precision and speed, providing a potential solution to relieve practitioners from manual segmentation tasks.

JOURNAL OF DENTISTRY (2022)

Article Computer Science, Artificial Intelligence

One DAG to Rule Them All

Federico Bolelli et al.

Summary: This paper presents novel strategies for optimizing the performance of binary image processing algorithms. These strategies are integrated into an open-source framework, GRAPHGEN, which automatically generates optimized C++ source code. The proposed algorithms generate decision trees with minimum average path-length, consider image pattern frequencies, and utilize DRAGs for state prediction and code compression. The experimental results demonstrate that the proposed approach significantly improves performance compared to existing algorithms on both CPU and GPU.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2022)

Article Radiology, Nuclear Medicine & Medical Imaging

Inferior alveolar canal segmentation based on cone-beam computed tomography

Xueqiong Wei et al.

Summary: This study proposes an IAC segmentation method based on CBCT images to effectively analyze the shape and position of the IAC. By enhancing the image contrast and generating smooth dental arch curves, the method successfully segments the smooth edges of the IAC. Experimental results demonstrate accurate reflection of the relationships between IAC and other structures in panoramic images without superimposition or geometric distortion.

MEDICAL PHYSICS (2021)

Article Computer Science, Artificial Intelligence

CHAOS Challenge- combined (CT-MR) healthy abdominal organ segmentation

A. Emre Kavur et al.

Summary: Abdominal organ segmentation has long been a comprehensive research field, with recent developments in deep learning introducing new state-of-the-art segmentation systems. However, the effects of DL model properties and parameters on performance are still difficult to interpret, and multi-tasking DL models often perform worse compared to organ-specific ones.

MEDICAL IMAGE ANALYSIS (2021)

Article Computer Science, Interdisciplinary Applications

TorchIO: A Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning

Fernando Perez-Garcia et al.

Summary: TorchIO is an open-source Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images for deep learning. It encourages good open-science practices, supports experiment reproducibility, and is version-controlled for precise citation. The modular library is compatible with other frameworks for deep learning with medical images.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2021)

Proceedings Paper Computer Science, Artificial Intelligence

Supporting Skin Lesion Diagnosis with Content-Based Image Retrieval

Stefano Allegretti et al.

Summary: This paper introduces a novel skin image retrieval system that utilizes deep learning and embedding network technology to assist in the fast diagnosis of dermatologists for skin lesions, improving diagnostic accuracy.

2020 25TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR) (2021)

Proceedings Paper Computer Science, Artificial Intelligence

Confidence Calibration for Deep Renal Biopsy Immunofluorescence Image Classification

Federico Pollastri et al.

Summary: In this study, state-of-the-art Convolutional Neural Networks are used to classify immunofluorescence in renal biopsy, with a focus on addressing the issue of overconfident outputs. The research demonstrates the successful application of Temperature Scaling (TS) for providing reliable probabilities in this context, showing good accuracy and reliability in a task with low inter-rater agreement.

2020 25TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR) (2021)

Proceedings Paper Computer Science, Artificial Intelligence

A Cone Beam Computed Tomography Annotation Tool for Automatic Detection of the Inferior Alveolar Nerve Canal

Cristian Mercadante et al.

Summary: Deep learning has achieved impressive results in various medical fields, but the requirement for large amounts of annotated data can be a challenge, particularly in medical imaging. Recent works have focused on detecting the Inferior Alveolar Nerve to prevent injuries during surgical procedures.

VISAPP: PROCEEDINGS OF THE 16TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS - VOL. 4: VISAPP (2021)

Article Computer Science, Artificial Intelligence

Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans

Michael Roberts et al.

Summary: Many machine learning-based approaches have been developed for the prognosis and diagnosis of COVID-19 from medical images. However, a systematic review found that current studies have methodological flaws, preventing their potential clinical utility. Recommendations are provided to address these issues for higher-quality model development.

NATURE MACHINE INTELLIGENCE (2021)

Article Computer Science, Information Systems

Augmenting data with GANs to segment melanoma skin lesions

Federico Pollastri et al.

MULTIMEDIA TOOLS AND APPLICATIONS (2020)

Article Multidisciplinary Sciences

Automatic mandibular canal detection using a deep convolutional neural network

Gloria Hyunjung Kwak et al.

SCIENTIFIC REPORTS (2020)

Article Multidisciplinary Sciences

Deep Learning Method for Mandibular Canal Segmentation in Dental Cone Beam Computed Tomography Volumes

Joel Jaskari et al.

SCIENTIFIC REPORTS (2020)

Article Urology & Nephrology

Evaluation of the Classification Accuracy of the Kidney Biopsy Direct Immunofluorescence through Convolutional Neural Networks

Giulia Ligabue et al.

CLINICAL JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY (2020)

Article Dentistry, Oral Surgery & Medicine

Study of Normal Anatomy of Mandibular Canal and its Variations in Indian Population Using CBCT

Arpita Komal et al.

JOURNAL OF MAXILLOFACIAL & ORAL SURGERY (2020)

Proceedings Paper Computer Science, Artificial Intelligence

Skin Lesion Segmentation Ensemble with Diverse Training Strategies

Laura Canalini et al.

COMPUTER ANALYSIS OF IMAGES AND PATTERNS, CAIP 2019, PT I (2019)

Article Dentistry, Oral Surgery & Medicine

An overview of deep learning in the field of dentistry

Jae-Joon Hwang et al.

IMAGING SCIENCE IN DENTISTRY (2019)

Article Dentistry, Oral Surgery & Medicine

Structural and ultrastructural analyses of bone regeneration in rabbit cranial osteotomy: Piezosurgery versus traditional osteotomes

Alexandre Anesi et al.

JOURNAL OF CRANIO-MAXILLOFACIAL SURGERY (2018)

Article Engineering, Biomedical

Automatic segmentation of mandibular canal in cone beam CT images using conditional statistical shape model and fast marching

Fatemeh Abdolali et al.

INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY (2017)

Article Computer Science, Artificial Intelligence

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

Vijay Badrinarayanan et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2017)

Article Multidisciplinary Sciences

Dermatologist-level classification of skin cancer with deep neural networks

Andre Esteva et al.

NATURE (2017)

Article Computer Science, Interdisciplinary Applications

Computer-based extraction of the inferior alveolar nerve canal in 3-D space

T Kondo et al.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2004)