Segmentation of Retinal Low-Cost Optical Coherence Tomography Images using Deep Learning

The treatment of age-related macular degeneration (AMD) requires continuous eye exams using optical coherence tomography (OCT). The need for treatment is determined by the presence or change of disease-specific OCT-based biomarkers. Therefore, the monitoring frequency has a significant influence on the success of AMD therapy. However, the monitoring frequency of current treatment schemes is not individually adapted to the patient and therefore often insufficient. While a higher monitoring frequency would have a positive effect on the success of treatment, in practice it can only be achieved with a home monitoring solution. One of the key requirements of a home monitoring OCT system is a computer-aided diagnosis to automatically detect and quantify pathological changes using specific OCT-based biomarkers. In this paper, for the first time, retinal scans of a novel self-examination low-cost full-field OCT (SELF-OCT) are segmented using a deep learning-based approach. A convolutional neural network (CNN) is utilized to segment the total retina as well as pigment epithelial detachments (PED). It is shown that the CNN-based approach can segment the retina with high accuracy, whereas the segmentation of the PED proves to be challenging. In addition, a convolutional denoising autoencoder (CDAE) refines the CNN prediction, which has previously learned retinal shape information. It is shown that the CDAE refinement can correct segmentation errors caused by artifacts in the OCT image.Comment: Accepted for SPIE Medical Imaging 2020: Computer-Aided Diagnosi

Vielversprechende Langzeitergebnisse zum Einsatz von Anastrozol zur Prävention von Brustkrebs bei postmenopausalen Hochrisikopatientinnen

Background!#!Re-entry devices are used regularly in subintimal recanalization of chronic occlusions of the iliac and femoro-popliteal arteries and significantly contribute to the high success rate of these interventions. However, the use in tibio-peroneal arteries has only been described in few cases so far. The present work is a retrospective evaluation of the Outback® re-entry device for gaining targeted true lumen access at the level of the tibio-peroneal arteries.!##!Methods!#!From 9/2017 until 10/2020 the Outback® catheter was used in case of failed spontaneous re-entry at the level of the tibio-peroneal arteries in 14 patients either instead of the usual retrograde approach via a pedal/distal-crural access (n = 11) or in combination with it (n = 3). Baseline demographic and clinical data, morphologic characteristics of the occlusions, procedural succedss, as well as the Society of Vascular Surgery (SVS) runoff score before and after revascularization were documented.!##!Results!#!All patients (median age: 78 years; range: 66-93) suffered from peripheral artery occlusive disease Rutherford stage 4 to 6 with a median lesion length of 12 cm (range: 7-35). Technical and procedural success was achieved in all 14 patients. The mean re-entry accuracy was 0.25 cm (range: 0-0.8). The SVS runoff score improved from a median of 14.5 (interquartile range IQR: 10.8-16.4) to 7 (IQR: 6.3-7) (p < 0.01).!##!Conclusions!#!The use of the Outback® catheter for targeted tibio-peroneal re-entry is associated with a high technical and procedural success rate and should be considered in case of otherwise failed ante- and retrograde recanalization