Carlos Ciller

• Doctor of Philosophy
• CEO at RetinAI Medical

The automatic segmentation of retinal layer structures enables clinically-relevant quantification and monitoring of eye disorders over time in OCT imaging. Eyes with late-stage diseases are particularly challenging to segment, as their shape is highly warped due to pathological biomarkers. In this context, we propose a novel fully Convolutional Neu...

Retinal swelling due to the accumulation of fluid is associated with the most vision-threatening retinal diseases. Optical coherence tomography (OCT) is the current standard of care in assessing the presence and quantity of retinal fluid and image-guided treatment management. Deep learning methods have made their impact across medical imaging and m...

We introduce a novel CNN-based feature point detector - GLAMpoints - learned in a semi-supervised manner. Our detector extracts repeatable, stable interest points with a dense coverage, specifically designed to maximize the correct matching in a specific domain, which is in contrast to conventional techniques that optimize indirect metrics. In this...

In this work we evaluated a postprocessing, customized automatic retinal OCT B-scan enhancement software for noise reduction, contrast enhancement and improved depth quality applicable to Heidelberg Engineering Spectralis OCT devices. A trained deep neural network was used to process images from an OCT dataset with ground truth biomarker gradings....

Purpose: To develop a reliable algorithm for the automated identification, localization, and volume measurement of exudative manifestations in neovascular age-related macular degeneration (nAMD), including intraretinal (IRF), subretinal fluid (SRF), and pigment epithelium detachment (PED), using a deep-learning approach. Methods: One hundred sev...

Objective This study validated the artificial intelligence (AI)-based algorithm LuxIA for screening more-than-mild diabetic retinopathy (mtmDR) from a single 45° colour fundus image of patients with diabetes mellitus (DM, type 1 or type 2) in Spain. Secondary objectives included validating LuxIA according to the International Clinical Diabetic Reti...

Aim To evaluate the impact of fluid volume fluctuations quantified with artificial intelligence in optical coherence tomography scans during the maintenance phase and visual outcomes at 12 and 24 months in a real-world, multicentre, national cohort of treatment-naïve neovascular age-related macular degeneration (nAMD) eyes. Methods Demographics, v...

Purpose Diabetic retinopathy (DR) is the leading cause of vision impairment in working-age adults. Automated screening can increase DR detection at early stages at relatively low costs. We developed and evaluated a cloud-based screening tool that uses artificial intelligence (AI), the LuxIA algorithm, to detect DR from a single fundus image. Metho...

Aim To explore associations between artificial intelligence (AI)-based fluid compartment quantifications and 12 months visual outcomes in OCT images from a real-world, multicentre, national cohort of naïve neovascular age-related macular degeneration (nAMD) treated eyes. Methods Demographics, visual acuity (VA), drug and number of injections data...

Purpose To develop a fully automated algorithm for accurate detection of fovea location in atrophic age-related macular degeneration (AMD), based on spectral-domain optical coherence tomography (SD-OCT) scans. Methods Image processing was conducted on a cohort of patients affected by geographic atrophy (GA). SD-OCT images (cube volume) from 55 eye...

Purpose: To develop and validate an automatic retinal pigment epithelial and outer retinal atrophy (RORA) progression prediction model for nonexudative age-related macular degeneration (AMD) cases in optical coherence tomography (OCT) scans. Methods: Longitudinal OCT data from 129 eyes/119 patients with RORA was collected and separated into trai...

Age-related macular degeneration (AMD) is a progressive retinal disease, causing vision loss. A more detailed characterization of its atrophic form became possible thanks to the introduction of Optical Coherence Tomography (OCT). However, manual atrophy quantification in 3D retinal scans is a tedious task and prevents taking full advantage of the a...

Purpose: We investigate which spectral domain-optical coherence tomography (SD-OCT) setting is superior when measuring subfoveal choroidal thickness (CT) and compared results to an automated segmentation software. Methods: Thirty patients underwent enhanced depth imaging (EDI)-OCT. B-scans were extracted in six different settings (W+N = white ba...

The automatic segmentation of retinal layer structures enables clinically-relevant quantification and monitoring of eye disorders over time in OCT imaging. Eyes with late-stage diseases are particularly challenging to segment, as their shape is highly warped due to pathological biomarkers. In this context, we propose a novel fully-Convolutional Neu...

Retinoblastoma and uveal melanoma are fast spreading eye tumors usually diagnosed by using 2D Fundus Image Photography (Fundus) and 2D Ultrasound (US). Diagnosis and treatment planning of such diseases often require additional complementary imaging to confirm the tumor extend via 3D Magnetic Resonance Imaging (MRI). In this context, having automati...

Automatic segmentation of eye structures and tumors. Five additional examples for the segmentation performed on retinoblastoma patients. a-b) Two examples including retinal detachment. c) Small tumor located close to the optic nerve. d) Smallest tumor in the dataset (≈20 voxels). T2w sequence does not show any sign of tumor. e) Mid-sized tumor clos...

Complementary results. Complete results comparing HM vs. PM vs. CM. Additional details about the classificacion performance for all 4 experiments (RF-STD, RF-EPSF, CNN-EPSF and CNN-STD) and for all patients. (XLSX)

T1w Gradient Echo (GE) VIBE Sequence. Detailed sequence information for reproducing the MRI acquisition. (PDF)

T2w Spin Echo (SE) Sequence. Detailed sequence information for reproducing the MRI acquisition. (PDF)

This paper aims to compare the metabolic effects of glucose-fructose co-ingestion (GLUFRU) with glucose alone (GLU) in exercising individuals with type 1 diabetes mellitus. Fifteen male individuals with type 1 diabetes (HbA1c 7.0% ± 0.6% (53 ± 7 mmol/mol)) underwent a 90 min iso-energetic continuous cycling session at 50% VO2max while ingesting com...

Optical Coherence Tomography (OCT) provides a unique ability to image the eye retina in 3D at micrometer resolution and gives ophthalmologist the ability to visualize retinal diseases such as Age-Related Macular Degeneration (AMD). While visual inspection of OCT volumes remains the main method for AMD identification, doing so is time consuming as e...

Aims/hypothesis: To investigate exercise-related fuel metabolism in intermittent high-intensity (IHE) and continuous moderate intensity (CONT) exercise in individuals with type 1 diabetes mellitus. Methods: In a prospective randomised open-label cross-over trial twelve male individuals with well-controlled type 1 diabetes underwent a 90 min iso-...

Aim: Depending on intensity, exercise may induce a strong hormonal and metabolic response, including acid-base imbalances and changes in microcirculation, potentially interfering with the accuracy of continuous glucose monitoring (CGM). The present study aimed at comparing the accuracy of the Dexcom G4 Platinum (DG4P) CGM during continuous moderat...

Proper delineation of ocular anatomy in 3-dimensional (3D) imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic resonance imaging (MRI) is presently used in clinical practice for diagnosis confirmation and treatment planning for treatment of retinoblastoma in infants, where it serves as a source of...

Ophthalmologists typically acquire different image modalities to diagnose eye pathologies. They comprise e.g., Fundus photography, Optical Coherence Tomography (OCT), Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Yet, these images are often complementary and do express the same pathologies in a different way. Some pathologies are o...

Delineation of ocular anatomy in 3D imaging involves a big challenge for ophthalmologists, mostly when developing the treatment planning for ocular diseases. Magnetic resonance imaging (MRI) is used today in clinical practice as a complementary source of information, together with fundus imaging or ultrasound, in treatment planning for retinoblasto...