Unit conversion for ‘flux’ output

[Jinze Li]

Dear Dr. Fang,

I recently started using MCX and had a few fundamental questions.

I want to use MCXLAB to simulate a 20mW uniform continuous light source illuminating a simplified biological tissue model, observing its light distribution and attenuation curve. However, when normalized, I observe that the magnitude of the output flux results is extremely large (approximately 10^8). Reviewing other posts, I see the default flux unit is 1/mm²/s. How should I modify my code to ensure the output flux corresponds to my 20mW light source and is converted to the unit mW/cm²?

Here is my code.

%% MCXLAB模型仿真

clear; clc; close all;

addpath('D:\mcxlab');

addpath('D:\mcxlab\matlab');

%% 1. 基本仿真参数

cfg.nphoton = 5e7;

cfg.tstart = 0;

cfg.tend = 5e-9;

cfg.tstep = 5e-9;

cfg.unitinmm = 0.01;

cfg.autopilot = 1;

cfg.gpuid = 1;

cfg.outputtype = 'flux';

%% 2. 体素模型 200×200×255

dimx = 200; dimy = 200; dimz = 255;

cfg.vol = zeros(dimx, dimy, dimz, 'uint8');

cfg.vol(:,:, 1:30) = 1; % 0.00–0.30 mm Scalp

cfg.vol(:,:,31:55) = 2; % 0.30–0.55 mm Skull

cfg.vol(:,:,56:155) = 3; % 0.55–1.55 mm CSF + Cortex

cfg.vol(:,:,156:255) = 4; % 1.55–2.55 mm Deep brain

%% 3. 光学参数（单位 mm⁻¹）

cfg.prop = [

0 0 1 1; % 0: 空气（外部）

0.018, 19.0, 0.9, 1.37; % 1: Scalp

0.016, 16.0, 0.9, 1.43; % 2: Skull

0.036, 22.0, 0.9, 1.37; % 3: Cortex

0.036, 22.0, 0.9, 1.37 % 4: Hippocampus

];

%% 4. 均匀面光源（200×200 体素全覆盖）

cfg.srctype = 'planar';

cfg.srcpos = [0, 0, 0]; % 左下角

cfg.srcdir = [0, 0, 1, 0];

cfg.srcparam1 = [dimx, 0, 0, 0]; % x 方向 200 体素

cfg.srcparam2 = [0, dimy, 0, 0]; % y 方向 200 体素

cfg.issrcfrom0 = 1;

%% 5. 边界与输出设置

cfg.isreflect = 1; % 开启外部边界反射

cfg.isnormalized = 1; % 默认就是 1（归一化）

%% 6. 运行仿真

tic;

f = mcxlab(cfg);

toc;

%% 7. 中心横断面（y=100）—— 正确量级

fluence_rate_cw = squeeze(f.data(:,100,:,1));

figure('Position',[100 100 950 700]);

imagesc(log10(fluence_rate_cw'));

colormap(jet); colorbar;

caxis([6.5 8.5]);

hold on;

% 层边界（白色虚线）

for z = [30 55 155 255]

plot([1 200], [z z], 'w--', 'LineWidth', 1.5);

end

% 坐标轴换成 mm

set(gca,'XTick',0:50:200,'XTickLabel',0:0.5:2);

set(gca,'YTick',0:50:255,'YTickLabel',0:0.5:2.55);

xlabel('X (mm)'); ylabel('Depth (mm)');

title('Log_{10}(Fluence Rate) - Center Slice (Uniform Planar Source)');

axis image;

% 1/e 深度

z_profile = squeeze(mean(mean(squeeze(f.data(:,:,:,1)), 1), 2));

[peak_val,peak_idx] = max(z_profile);

threshold = peak_val/exp(1);

idx1e = find(z_profile(peak_idx:end) <= threshold,1,'first') + peak_idx - 1;

depth_1e = (idx1e-0.5)*cfg.unitinmm;

plot([1 200], [idx1e idx1e], 'b-', 'LineWidth', 2.5);

text(10, idx1e-8, sprintf('1/e depth: %.2f mm', depth_1e), ...

'Color','blue','FontSize',12,'FontWeight','bold');

% 诊断 fluence 范围

fluence_log_data = log10(fluence_rate_cw);

min_val = min(fluence_log_data(fluence_log_data > 0));

max_val = max(fluence_log_data(:));

fprintf('实际 Log10(Fluence) 范围是：[%.2f, %.2f]\n', min_val, max_val);

%% 8. 衰减曲线

z_mm = ((1:dimz)-0.5)*cfg.unitinmm; % 真实深度 mm

figure;

semilogy(z_mm, z_profile, 'b-', 'LineWidth', 2); hold on;

semilogy(z_mm(peak_idx), peak_val, 'ro', 'MarkerSize', 8, 'MarkerFaceColor','r');

semilogy([0 2.6], [threshold threshold], 'r--','LineWidth',1.5);

semilogy(depth_1e, threshold, 'rp','MarkerSize',12,'MarkerFaceColor','r');

grid on; xlabel('Depth (mm)'); ylabel('Fluence Rate ');

title(sprintf('Center Profile - 1/e depth = %.2f mm (Peak = %.2e)', depth_1e, peak_val));

xlim([0 2.6]);

legend('Fluence rate','Peak','1/e threshold','1/e depth','Location','southwest');

fprintf('=== 诊断信息 ===\n');

fprintf('f.data 维度: %s\n', mat2str(size(f.data)));

fprintf('峰值 fluence rate = %.3e\n', peak_val);

fprintf('1/e 穿透深度 = %.2f mm\n', depth_1e);

Kind regards, 

Jinze Li