• No se han encontrado resultados

TítuloAutomatic identification and characterization of the epiretinal membrane in OCT images

N/A
N/A
Protected

Academic year: 2020

Share "TítuloAutomatic identification and characterization of the epiretinal membrane in OCT images"

Copied!
16
0
0

Texto completo

Loading

Figure

Fig. 1: Different epiretinal membrane appearances in the OCT scans. The arrow indicates the specific localization of the ERM, a reflective layer on the top of the ILM
Fig. 3: ILM segmentation by the active contour model. The red points represent the ILM layer identification.
Fig. 4: Definition of the region of interest around an analyzed point. (a): Definition of the vertical window around the central point, with a size of 17 × 85 pixels
Fig. 5: 2-class and 3-class approximations. (1) Red symbolizes the ERM presence. (1a) Red symbolizes the ERM on top of the ILM
+7

Referencias

Documento similar

Then, the bifurcation points that were detected as the method presented in the paper were used later to measure the bifurcation angles of the retinal vascular tree through the

Another notable work in the identification of Academic Rising Stars using machine learning came in Scientometric Indicators and Machine Learning-Based Models for Predict- ing

Selective identification, characterization and determination of dissolved silver(I) and silver nanoparticles based on single particle detection by inductively coupled plasma

 The expansionary monetary policy measures have had a negative impact on net interest margins both via the reduction in interest rates and –less powerfully- the flattening of the

Jointly estimate this entry game with several outcome equations (fees/rates, credit limits) for bank accounts, credit cards and lines of credit. Use simulation methods to

Thus, we have undertaken a wide sequence comparison using the NCBI digital databases, and through the identification of lantana specific sequences in the

Of special concern for this work are outbreaks formed by the benthic dinoflagellate Ostreopsis (Schmidt), including several species producers of palytoxin (PLTX)-like compounds,

Again, as in Takada's method, ELL (efficient) identification in the limit is possible by using a regular language (efficient) identification method, and this requires the