Calculate the central magnification of an eye - camera system
This integration demonstrates how PAROS can be used to calculate the central magnification of a fundus image. More information can be found at our GitHub repository.
Check the code Read the paper Edit the demo
Warning
This example is not intended for medical use and does not allow to customize camera-related parameters.
To calculate the magnification of a fundus image, enter the parameters of the eye in the calculator below. If you do not have all required parameters, it is possible to estimate some parameters:
- The posterior corneal curvature can be estimated as \(0.81 \times \mathrm{anterior\ corneal\ curvature}\). To do this, click the Estimate posterior corneal curvature button.
- The posterior lens curvature can be fitted from the spherical equivalent of refraction. To do this, click the Fit posterior lens curvature button.
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## file: app.py
from shiny import reactive
from shiny.express import input, render, ui
from dataclasses import dataclass
from pandas import Series, DataFrame
def import_paros():
"""Hack needed because importing sympy (via paros) breaks printing"""
from PAROS.fundscale import Eye, Camera, PhakicIOL, calculate_magnification
return Eye, Camera, PhakicIOL, calculate_magnification
ui.tags.style("table { display: block; }", "th, td { padding: 0px 10px 0px 0px; }")
with ui.card():
ui.card_header("Eye model parameters")
with ui.card():
ui.input_select(
"model_type",
"Model type",
("Phakic", "Pseudophakic", "pIOL"),
selected="Phakic",
)
with ui.card():
with ui.layout_columns():
ui.input_numeric(
"r_corf", "Anterior corneal curvature (mm)", 7.72, min=0, step=0.1
)
ui.input_numeric(
"r_corb", "Posterior corneal curvature (mm)", 6.50, min=0, step=0.1
)
ui.input_numeric(
"r_lensf", "Anterior lens curvature (mm)", 10.2, min=0, step=0.5
)
ui.input_numeric(
"r_lensb", "Posterior lens curvature (mm)", 6.0, min=0, step=0.5
)
ui.input_numeric("d_cor", "Corneal thickness (mm)", 0.55, min=0, step=0.1)
ui.input_numeric(
"d_acd", "Anterior chamber depth (mm)", 3.05, min=0, step=0.1
)
ui.input_numeric(
"d_lens", "Crystalline lens thickness (mm)", 4, min=0, step=0.5
)
ui.input_numeric(
"d_vitr", "Vitreous chamber depth (mm)", 16.3203, min=0, step=0.5
)
ui.input_numeric(
"se", "Spherical eq. of refraction (D)", 0, min=-10, max=10, step=0.5
)
with ui.panel_conditional("input.model_type == 'pIOL'"):
ui.input_numeric("piol_power", "pIOL power", 9, step=0.5)
with ui.card():
with ui.layout_columns():
with ui.tooltip(placement="bottom"):
ui.input_action_button(
"estimate_r_corb", "Estimate posterior corneal curvature"
)
"Calculate the posterior cornea curvature as 0.81 × anterior corneal curvature"
with ui.tooltip(placement="bottom"):
ui.input_action_button("fit_r_lensb", "Fit posterior lens curvature")
"Fit the lens back curvature to the specified spherical equivalent"
with ui.card():
ui.card_header("Camera parameters")
ui.markdown(
"See our publication for an explanation of the camera-specific parameters. "
"Parameters used in this demo: \n"
"<table>"
"<tr><td><strong>Condenser lens power</strong></td><td>37.6 D</td></tr>"
"<tr><td><strong>First order correction term</strong></td><td>0.035</td></tr>"
"</table>"
)
def phakic_eye(Eye):
phakic_geometry = {
"R_corF": input.r_corf() * -(10**-3),
"R_corB": input.r_corb() * -(10**-3),
"R_lensF": input.r_lensf() * -(10**-3),
"R_lensB": input.r_lensb() * 10**-3,
"D_cor": input.d_cor() * 10**-3,
"D_ACD": input.d_acd() * 10**-3,
"D_lens": input.d_lens() * 10**-3,
"D_vitr": input.d_vitr() * 10**-3,
"SE": input.se(),
}
# Define a phakic eye model
return Eye(
name="phakic",
geometry=phakic_geometry,
NType="Navarro",
refraction=phakic_geometry["SE"],
)
def pseudophakic_eye(Eye):
pseudophakic_geometry = {
"R_corF": input.r_corf() * -(10**-3),
"R_corB": input.r_corb() * -(10**-3),
"R_lensF": input.r_lensf() * -(10**-3),
"R_lensB": input.r_lensb() * 10**-3,
"D_cor": input.d_cor() * 10**-3,
"D_ACD": input.d_acd() * 10**-3,
"D_lens": input.d_lens() * 10**-3,
"D_vitr": input.d_vitr() * 10**-3,
"SE": input.se(),
}
return Eye(
name="IOL",
geometry=pseudophakic_geometry,
model_type="VughtIOL",
NType="VughtIOL",
refraction=pseudophakic_geometry["SE"],
)
def piol_eye(Eye, PhakicIOL):
piol_geometry = {
"R_corF": input.r_corf() * -(10**-3),
"R_corB": input.r_corb() * -(10**-3),
"R_lensF": input.r_lensf() * -(10**-3),
"R_lensB": input.r_lensb() * 10**-3,
"D_cor": input.d_cor() * 10**-3,
"D_ACD": input.d_acd() * 10**-3,
"D_lens": input.d_lens() * 10**-3,
"D_vitr": input.d_vitr() * 10**-3,
"SE": input.se(),
}
piol_data = PhakicIOL(
power=input.piol_power(),
thickness=0.2e-3,
refractive_index=1.47,
lens_distance=0.5e-3,
)
return Eye(
name="pIOL",
geometry=piol_geometry,
NType="Navarro",
refraction=piol_geometry["SE"],
pIOL=piol_data,
)
@reactive.calc
def eye_model():
Eye, _, PhakicIOL, _ = import_paros()
if input.model_type() == "Phakic":
return phakic_eye(Eye)
if input.model_type() == "Pseudophakic":
return pseudophakic_eye(Eye)
if input.model_type() == "pIOL":
return piol_eye(Eye, PhakicIOL)
raise ValueError(f"{input.model_type()} is not supported")
@reactive.effect
@reactive.event(input.estimate_r_corb)
def update_r_corb():
ui.update_numeric("r_corb", value=round(0.81 * input.r_corf(), 2))
@reactive.effect
@reactive.event(input.fit_r_lensb)
def update_r_lensb():
eye = eye_model()
lens_curvature, _ = eye.adjust_lens_back(input.se(), update_model=False)
ui.update_numeric("r_lensb", value=1000 * float(lens_curvature))
with ui.card():
ui.card_header("Result")
@render.ui()
def calculate():
_, Camera, PhakicIOL, calculate_magnification = import_paros()
eye = eye_model()
camera_f_cond = 0.02657
camera_a1 = 0.03481
camera = Camera(F_cond=camera_f_cond, a1=camera_a1)
lens_back_curvature, glasses_curvature = eye.adjust_lens_back(
eye.geometry["SE"], update_model=True
)
magnification, *_ = calculate_magnification(eye, camera)
return ui.markdown(
f"**Magnification:** {abs(magnification):.2f}"
)
## file: requirements.txt
paros >= 1.0.1
sympy