Checkout our newly submitted paper on a highly scalable and memory efficient MMC approach to model very complex tissue structures. The implicit MMC (iMMC) code was developed by PhD student Yaoshen Yuan, and will be available in our next MMC release.
Also check out this cool animation: https://twitter.com/FangQ/status/1315417111708069888
Full citation information:
Shijie Yan and Qianqian Fang, "Hybrid mesh and voxel based Monte Carlo algorithm for accurate and efficient photon transport modeling in complex bio-tissues," Biomed. Opt. Express 11, 6262-6270 (2020)
Code will be released shortly.
MCX_MMC v2020 was announced. They have packed numerous commits accumulated over the past 16 months, including the first MCX-CL release that matches MCX in features, the first GPU-based MMC, win installer, and saving #openjdata outputs.
Get your copy from http://mcx.space/wiki/?Get here].
With the kind support from many of our users, the MCX grant has been successfully renewed! Over the past 5 years, the MCX project has grown tremendously. We have more than quadrupled the total number of registered users (500 to 2400) and the number of citations (250 to 1100). Many of the new methods and features have been developed, published, and added to our open-source toolkit; mcx/mmc are now available in Fedora and Winget, and will soon become available in Debian/Ubuntu. Our software has found use in a wide range of applications and was increasingly tested and trusted by many. We feel truly honored to contribute our small part to many of your endeavors, and would be very much eager to share our new development with you down the path. In the next chapter of the MCX project, we have planed many exciting new milestones, many of which are already under heavy development. Stay tuned, more will come!
See our road-map for the next 4 years.
We created a Windows all-in-one installer for our MCX/MMC users to automate the installation and settings on Windows. It contains both binaries and MATLAB toolboxes for all of our software components.
Nightly build installer is at http://mcx.space/nightly/win64/
Give it a try!
See screenshots in this tweet: https://twitter.com/FangQ/status/1279935567095087106
Congratulations to our PhD student Shijie Yan for publishing a new paper on Optics Letters. In this method, one can simultaneously simulate many pattered light sources using our MCX/MMC simulators. This feature is now supported in our open-source software.
Shijie Yan, Ruoyang Yao, Xavier Intes, and Qianqian Fang, "Accelerating Monte Carlo modeling of structured-light-based diffuse optical imaging via “photon sharing”," Opt. Lett. 45, 2842-2845 (2020)
Download PDF from our preprint on biorxiv.
Brain2Mesh is a MATLAB/Octave based 3D mesh generation toolbox dedicated to the creation of high-quality multi-layered brain mesh models. The details of this toolbox is described in this newly published paper on Neurophotonics:
Anh Phong Tran†, Shijie Yan†, Qianqian Fang*, (2020) "Improving model-based fNIRS analysis using mesh-based anatomical and light-transport models," Neurophotonics, 7(1), 015008
Brain2mesh is open-source! Download it from http://mcx.space/brain2mesh/
Our PhD student Yaoshen Yuan's latest paper on photobiomodulation dosage over a wide span of age groups, ranging from 5 to 89 years old, is now published in Neurophotonics:
Yuan Y, Cassano P, Fang Q*, (2020) “Transcranial Photobiomodulation with Near-Infrared Light from Childhood to Elderliness: Simulation of Dosimetry",Neurophotonics, 7(1), 015009
The paper focuses on the speed improvement of mesh-based MC (DMMC) photo transport simulator by using a coarsely tessellated tetrahedral mesh for ray-tracing computation and an independent voxelated grid for output data storage. DMMC is able to improve the speed by 1.3 × to 2.9 × for various scattering settings. This paper is now available online.
Shijie Yan, Anh Phong Tran, Qianqian Fang, "Dual-grid mesh-based Monte Carlo algorithm for efficient photon transport simulations in complex three-dimensional media," J. Biomed. Opt. 24(2) 020503 (20 February 2019) https://doi.org/10.1117/1.JBO.24.2.020503
DMMC has been integrated into current version of MMC.
In collaboration with Prof. Paolo Cassano from MGH, we performed a Monte Carlo simulation based study on the illumination positions (transcranial and intranasal) and 3D dosimetry for photobiomodulation (low-light therapy) using our in-house simulators to better guide the design of PMB treatment procedures and devices. This paper is in press on Neurophotonics.
Tran AP+, Cassano P+, Katnani H, Bleier BS, Hamblin MR, Yuan Y, Fang Q*, (2019) “Selective photobiomodulation for emotion regulation: model-based dosimetry study,” Neurophotonics 6(1) 015004, PMCID: PMC6366475
Yaoshen Yuan, Leiming Yu, Zafer Doğan, Qianqian Fang*, "Graphics processing units-accelerated adaptive non-local means filter for denoising three-dimensional Monte Carlo photon transport simulations," J. of Biomedical Optics, 23(12), 121618 (2018).
Open source code in Github.
Find the abstract in our Publications page
After nearly 10 years of continuous development, it is our great pleasure to announce that MCX 1.0 (v2018) has finally arrived! In the meantime, MMC has also arrived at its v1.0 milestone, after its initially publication in 2010. Moreover, we also proudly announce the first stable release of MCX-OpenCL (or MCXCL) - a "clone" of MCX that can run on nearly all CPUs and GPUs across many vendors.
Researchers at the Boston Children's Hospital (Jason Sutin, Ivy Lin, Ellen Grant, and Julia Tatz) had ported MCX to the cloud using the Redhat Kubernetes and containers, and Prof. Ellen Grant will give a demo of the software during the Redhat Developer Conference this Wed.
For more details, including tutorials from the event, click here.
We've also documented the process of building the GPU rack below:
Optics Engineering We are also looking for a postdoc with a background in optical instrumentation, medical device design, and mobile-app development. A strong electrical engineering background would be a plus. Apply here!
Computational Biophotonics This position is perfect for someone with a strong background in computational algorithm development, GPU computing, and computational physics. Proficiency in C/matlab software development is a necessity. Apply here!