AIMC Topic: Retinal Neoplasms

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Learning feature dependencies for precise tumor region detection and segmentation in optical coherence tomography images.

International ophthalmology
PURPOSE: Accurate segmentation of tumor-infected regions in retinal Optical Coherence Tomography (OCT) images is critical for early diagnosis and clinical decision-making. However, conventional deep learning and transformer-based models often struggl...

A noninvasive machine learning model using a complete blood count for screening of primary vitreoretinal lymphoma.

Nature communications
Primary vitreoretinal lymphoma (PVRL) is a rare and aggressive intraocular malignancy that is frequently misdiagnosed because of its nonspecific early manifestations and the lack of effective screening tools. We conduct a multicentre case-control stu...

Machine learning demonstrates clinical utility in distinguishing retinoblastoma from pseudo retinoblastoma with RetCam images.

Ophthalmic genetics
BACKGROUND: Retinoblastoma is diagnosed and treated without biopsy based solely on appearance (with the indirect ophthalmoscope and imaging). More than 20 benign ophthalmic disorders resemble retinoblastoma and errors in diagnosis continue to be made...

Artificial intelligence methods in diagnosis of retinoblastoma based on fundus imaging: a systematic review and meta-analysis.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
BACKGROUND: Artificial intelligence (AI) algorithms for the detection of retinoblastoma (RB) by fundus image analysis have been proposed as a potentially effective technique to facilitate diagnosis and screening programs. However, doubts remain about...

Automatic retinoblastoma screening and surveillance using deep learning.

British journal of cancer
BACKGROUND: Retinoblastoma is the most common intraocular malignancy in childhood. With the advanced management strategy, the globe salvage and overall survival have significantly improved, which proposes subsequent challenges regarding long-term sur...

Artificial intelligence and machine learning in ocular oncology, retinoblastoma (ArMOR).

Indian journal of ophthalmology
PURPOSE: To test the accuracy of a trained artificial intelligence and machine learning (AI/ML) model in the diagnosis and grouping of intraocular retinoblastoma (iRB) based on the International Classification of Retinoblastoma (ICRB) in a larger coh...

Ultrashort ssDNA in Retinoblastoma Patients Blood Plasma Detected by a Novel High Resolution HPLC Technique: a Preliminary Report.

Acta medica (Hradec Kralove)
A significant population of ultrashort (50-150n) single-stranded DNA fragments were found in exosome-free blood plasma of retinoblastoma patients (6.84 ng mL-1), but not in plasma of healthy donors. An original high resolution HPLC technique has been...