4.7 Article

End-to-End Deep-Learning-Based Diagnosis of Benign and Malignant Orbital Tumors on Computed Tomography Images

Related references

Note: Only part of the references are listed.
Article Surgery

Deep Learning-Based CT Radiomics for Feature Representation and Analysis of Aging Characteristics of Asian Bony Orbit

Zhu Li et al.

Summary: This paper proposes a new method for automatic segmentation of the bony orbit and extraction and classification of aging features based on depth learning. The preliminary validation of the aging mode of the bony orbit contour is achieved. The high-precision identification of bony orbit contour and aging features using convolutional neural networks is demonstrated. It is found that bone resorption is more obvious in the superior orbital rim than in the inferior orbital rim, while overall shape features do not change significantly with aging.

JOURNAL OF CRANIOFACIAL SURGERY (2022)

Article Radiology, Nuclear Medicine & Medical Imaging

Imaging Findings of Pediatric Orbital Masses and Tumor Mimics

Annie K. Joseph et al.

Summary: Pediatric orbital masses encompass a wide range of benign and malignant entities, including developmental anomalies, primary and secondary malignancies, and metastatic diseases. Clinical symptoms and signs are often insufficient for differentiation, and imaging is essential for narrowing down the diagnosis and determining the most appropriate management strategy. MRI is the primary imaging modality, with ultrasound and CT playing complementary roles.

RADIOGRAPHICS (2022)

Review Radiology, Nuclear Medicine & Medical Imaging

Application of Deep Learning in Breast Cancer Imaging

Luuk Balkenende et al.

Summary: This review provides an overview of the current state of deep learning research in breast cancer imaging. Breast imaging is crucial for early detection, monitoring, and evaluating breast cancer. Digital mammography, digital breast tomosynthesis, ultrasound, and magnetic resonance imaging are commonly used modalities for breast imaging, which can be digitized and applied with deep learning. Studies have shown that deep learning algorithms perform similarly or even better than radiologists in breast cancer imaging.

SEMINARS IN NUCLEAR MEDICINE (2022)

Article Anatomy & Morphology

Aging of Chinese bony orbit: automatic calculation based on UNet plus plus and connected component analysis

Lei Pan et al.

Summary: This study presents an automatic segmentation method for bony orbit based on deep learning, and automatically calculates the area and height of the segmented orbital contour. Analysis of craniofacial CT scanning data of 595 Chinese individuals showed that the bony orbital area changes with age and differs between males and females.

SURGICAL AND RADIOLOGIC ANATOMY (2022)

Review Health Care Sciences & Services

U-Net-Based Medical Image Segmentation

Xiao-Xia Yin et al.

Summary: This paper summarizes the characteristics and classifications of medical image segmentation technologies based on U-Net structure variants, introduces commonly used loss functions, evaluation parameters, and modules; it is of great significance for obtaining accurate segmentation results and improving segmentation performance.

JOURNAL OF HEALTHCARE ENGINEERING (2022)

Review Cell Biology

Orbital and eyelid diseases: The next breakthrough in artificial intelligence?

Xiao-Li Bao et al.

Summary: This paper retrospectively summarizes different aspects of imaging data in AI-related research on orbital and eyelid diseases, and discusses the advantages and limitations of this research field.

FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY (2022)

Review Health Care Sciences & Services

U-Net-Based Medical Image Segmentation

Xiao-Xia Yin et al.

Summary: This paper summarizes the medical image segmentation technologies based on the U-Net structure variants and introduces the related methodology, loss functions, evaluation parameters, and modules commonly applied to segmentation in medical imaging, providing a good reference for future research.

JOURNAL OF HEALTHCARE ENGINEERING (2022)

Article Radiology, Nuclear Medicine & Medical Imaging

Bag-of-features-based radiomics for differentiation of ocular adnexal lymphoma and idiopathic orbital inflammation from contrast-enhanced MRI

Yuqing Hou et al.

Summary: The BOF-based radiomics is effective in differentiating between OAL and IOI. The method shows potential for improved differentiation when combined with data augmentation, and performs better compared to human radiological diagnosis.

EUROPEAN RADIOLOGY (2021)

Review Ophthalmology

Orbital and ocular adnexal lymphoma: a review of epidemiology and prognostic factors in Taiwan

Cherng-Ru Hsu et al.

Summary: This study investigated the clinical features and prognostic outcomes of patients with orbital and ocular adnexal lymphoma in Taiwan. MALT lymphoma was the most common subtype, and patients with MALT lymphoma, FL, SLL, and earlier stage disease had better outcomes compared to those with high grade lymphoma and advanced stage disease.
Review Clinical Neurology

Typical Orbital Pathologies: Hemangioma

Christopher M. Low et al.

Summary: This article reviews the two distinct types of orbital hemangiomas: infantile hemangiomas and cavernous hemangiomas, focusing on their natural history, clinical presentation, and management teams and approaches. Each type of hemangioma is illustrated with an example case, along with pearls and tips for readers to take away.

JOURNAL OF NEUROLOGICAL SURGERY PART B-SKULL BASE (2021)

Review Cardiac & Cardiovascular Systems

Clinical Research Machine Learning Compared With Conventional Statistical Models for Predicting Myocardial Infarction Readmission and Mortality: A Systematic Review

Sung Min Cho et al.

Summary: This review compared the application of machine learning and conventional statistical modeling in predicting prognosis for patients with myocardial infarction from 2000 to 2020, finding that machine learning algorithms generally had higher C-indexes for predicting death or readmission after MI compared to traditional statistical modeling. Further studies are needed to validate these findings and adhere to clinical quality standards for prognosis research.

CANADIAN JOURNAL OF CARDIOLOGY (2021)

Article Oncology

Differentiate cavernous hemangioma from schwannoma with artificial intelligence (AI)

Shaowei Bi et al.

ANNALS OF TRANSLATIONAL MEDICINE (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

Workload for radiologists during on-call hours: dramatic increase in the past 15 years

R. J. M. Bruls et al.

INSIGHTS INTO IMAGING (2020)

Review Ophthalmology

Orbital lymphoma

Tine Gadegaard Olsen et al.

SURVEY OF OPHTHALMOLOGY (2019)

Review Ophthalmology

Diagnosis of orbital mass lesions: clinical, radiological, and pathological recommendations

Ilse Mombaerts et al.

SURVEY OF OPHTHALMOLOGY (2019)

Review Ophthalmology

Artificial intelligence and deep learning in ophthalmology

Daniel Shu Wei Ting et al.

BRITISH JOURNAL OF OPHTHALMOLOGY (2019)

Article Radiology, Nuclear Medicine & Medical Imaging

MR-based radiomics signature in differentiating ocular adnexal lymphoma from idiopathic orbital inflammation

Jian Guo et al.

EUROPEAN RADIOLOGY (2018)

Article Computer Science, Interdisciplinary Applications

Classification of CT brain images based on deep learning networks

Xiaohong W. Gao et al.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2017)

Article Radiology, Nuclear Medicine & Medical Imaging

Safe Use of Contrast Media: What the Radiologist Needs to Know

Katrina R. Beckett et al.

RADIOGRAPHICS (2015)

Article Radiology, Nuclear Medicine & Medical Imaging

Assessment of dynamic contrast-enhanced magnetic resonance imaging in the differentiation of malignant from benign orbital masses

Ying Yuan et al.

EUROPEAN JOURNAL OF RADIOLOGY (2013)

Article Oncology

Radiomics: Extracting more information from medical images using advanced feature analysis

Philippe Lambin et al.

EUROPEAN JOURNAL OF CANCER (2012)

Review Ophthalmology

Orbital masses: CT and MRI of common vascular lesions, benign tumors, and malignancies

Sarah N. Khan et al.

SAUDI JOURNAL OF OPHTHALMOLOGY (2012)

Review Radiology, Nuclear Medicine & Medical Imaging

Orbital lymphoma: imaging features and differential diagnosis

Gema Priego et al.

INSIGHTS INTO IMAGING (2012)

Article Clinical Neurology

Differentiation between benign and malignant orbital tumors at 3-T diffusion MR-imaging

Ahmed Abdel Khalek et al.

NEURORADIOLOGY (2011)

Editorial Material Ophthalmology

Cavernous Hemangioma of the Orbital Apex: Pathogenetic Considerations in Surgical Management

Gerald J. Harris

AMERICAN JOURNAL OF OPHTHALMOLOGY (2010)

Article Radiology, Nuclear Medicine & Medical Imaging

Value of MR imaging in the differentiation of benign and malignant orbital tumors in adults

Junfang Xian et al.

EUROPEAN RADIOLOGY (2010)

Article Ophthalmology

Treatment and long-term outcome of patients with orbital cavernomas

AF Scheuerle et al.

AMERICAN JOURNAL OF OPHTHALMOLOGY (2004)

Article Ophthalmology

Orbital tumors in the older adult population

H Demirci et al.

OPHTHALMOLOGY (2002)