AIMC Topic: Jaw Neoplasms

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CrossViT with ECAP: Enhanced deep learning for jaw lesion classification.

International journal of medical informatics Oct 28, 2024
BACKGROUND: Radiolucent jaw lesions like ameloblastoma (AM), dentigerous cyst (DC), odontogenic keratocyst (OKC), and radicular cyst (RC) often share similar characteristics, making diagnosis challenging. In 2021, CrossViT, a novel deep learning appr...
Humans Ameloblastoma Jaw Neoplasms Jaw Diseases Retrospective Studies Deep Learning Radiography, Panoramic
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Deep convolutional neural network for automatic segmentation and classification of jaw tumors in contrast-enhanced computed tomography images.

International journal of oral and maxillofacial surgery Oct 15, 2024
The purpose of this study was to evaluate the performance of convolutional neural network (CNN)-based image segmentation models for segmentation and classification of benign and malignant jaw tumors in contrast-enhanced computed tomography (CT) image...
Thailand Convolutional Neural Networks Contrast Media Tomography, X-Ray Computed Jaw Neoplasms Humans Female Neural Networks, Computer Male Retrospective Studies
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New perspectives in the differential diagnosis of jaw lesions: Machine learning and inflammatory biomarkers.

Journal of stomatology, oral and maxillofacial surgery May 7, 2024
This study aimed to assess the diagnostic performance of a machine learning approach that utilized radiomic features extracted from Cone Beam Computer Tomography (CBCT) images and inflammatory biomarkers for distinguishing between Dentigerous Cysts (...
Biomarkers Retrospective Studies Female Aged Young Adult Diagnosis, Differential Adult Odontogenic Cysts Cone-Beam Computed Tomography Dentigerous Cyst Ameloblastoma Humans Inflammation Male Machine Learning Jaw Neoplasms Decision Trees Middle Aged Adolescent Jaw Diseases
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Diagnostic capability of artificial intelligence tools for detecting and classifying odontogenic cysts and tumors: a systematic review and meta-analysis.

Oral surgery, oral medicine, oral pathology and oral radiology Mar 19, 2024
OBJECTIVE: To evaluate the diagnostic capability of artificial intelligence (AI) for detecting and classifying odontogenic cysts and tumors, with special emphasis on odontogenic keratocyst (OKC) and ameloblastoma.
Algorithms Cone-Beam Computed Tomography Odontogenic Tumors Radiography, Panoramic Humans Odontogenic Cysts Ameloblastoma Artificial Intelligence Jaw Neoplasms
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Evaluation of deep learning for detecting intraosseous jaw lesions in cone beam computed tomography volumes.

Oral surgery, oral medicine, oral pathology and oral radiology Oct 16, 2023
OBJECTIVE: The study aim was to develop and assess the performance of a deep learning (DL) algorithm in the detection of radiolucent intraosseous jaw lesions in cone beam computed tomography (CBCT) volumes.
Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Jaw Neoplasms Sensitivity and Specificity Deep Learning Cone-Beam Computed Tomography Jaw Diseases Humans Software Algorithms
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Deep learning based diagnosis for cysts and tumors of jaw with massive healthy samples.

Scientific reports Feb 3, 2022
We aimed to develop an explainable and reliable method to diagnose cysts and tumors of the jaw with massive panoramic radiographs of healthy peoples based on deep learning, since collecting and labeling massive lesion samples are time-consuming, and ...
Radiographic Image Interpretation, Computer-Assisted Deep Learning Humans Jaw Cysts Predictive Value of Tests Reproducibility of Results Radiography, Panoramic Jaw Neoplasms Case-Control Studies
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CBCT radiomics features combine machine learning to diagnose cystic lesions in the jaw.

Dento maxillo facial radiology Jul 1, 2025
OBJECTIVE: The aim of this study was to develop a radiomics model based on cone beam CT (CBCT) to differentiate odontogenic cysts (OCs), odontogenic keratocysts (OKCs), and ameloblastomas (ABs).
Sensitivity and Specificity Radiomics Male Retrospective Studies Female Adult Odontogenic Cysts Middle Aged Ameloblastoma Humans Cone-Beam Computed Tomography Jaw Neoplasms Machine Learning Diagnosis, Differential
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Application of machine learning in the preoperative radiomic diagnosis of ameloblastoma and odontogenic keratocyst based on cone-beam CT.

Dento maxillo facial radiology Jun 28, 2024
OBJECTIVES: Preoperative diagnosis of oral ameloblastoma (AME) and odontogenic keratocyst (OKC) has been a challenge in dentistry. This study uses radiomics approaches and machine learning (ML) algorithms to characterize cone-beam CT (CBCT) image fea...
Ameloblastoma Jaw Neoplasms Diagnosis, Differential Radiographic Image Interpretation, Computer-Assisted Odontogenic Cysts Adult Radiomics Male Middle Aged Adolescent Cone-Beam Computed Tomography Retrospective Studies Female Aged Humans Machine Learning Algorithms
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