Data Transmission via Multimode Fibres for Medical Imaging and Telecommunication

Summary: a cost-effective and reliable data transmission method based on a time-efficient characterisation of multimode fibers, which can be used in several applications, including medical imaging and telecommunication systems.


Multimode fibers (MMFs) are large core optical fibers that are commonly used to transmit information with light in telecommunications. Researchers at King’s developed a novel data transmission method based on MMFs, after discovering that under specific conditions the input and output intensity distributions of MMFs have a pseudo-linear behaviour. This allows to overcome a well-known problem associated to MMFs signal transmission in a time-efficient and cost-effective way. The proposed method can be applied to telecommunication systems, ultrasound imaging, endoscopic probes, as well as deep tissue optical microscopy, optogenetics, micro-manipulation, laser microsurgery, laser-induced thermal therapy and optical microscopy.


MMFs have been increasingly attractive for applications in medical imaging, as they are cost effective, allow to transmit images having high pixel density and to miniaturise probes for in-vivo visualisation.

Traditional imaging methods that use MMFs suffer from modal dispersion and mode coupling, with the subsequent formation of random-like speckle patterns on the output images. Previous known methods have tried to overcome this limitation through the characterisation of MMFs transmission matrixes, i.e. complex-valued matrixes, which connects the input and the output signals transported via MMFs with transmission constants. Each element of such transmission matrixes should contain the amplitude and the phase of the signal.

However, traditional sensors are only able to detect the amplitude of a signal, but not its phase. The known methods are thus able to capture the signal phase only using further sensors based on holographic systems or via deep-learning techniques. However, holographic systems are cumbersome and may affect the stability of the measurements, while deep learning techniques require large amount of data to be trained and work only with images similar to the ones of the training dataset.


The data transmission method developed by Researchers at King’s allows to overcome the problems associated with the characterisation of MMFs signals, without requiring further holographic sensors nor the preliminary acquisition of large datasets. The method is time and computationally efficient and can be easily implemented on most of the processors available on the market. On an experimental setup, the characterisation of a MMF was performed within ~16 s (-8 s for data acquisition and ~8 s for processing) using input images having 1024 pixels.

Furthermore, the method can work with any type of signal, as it is able to capture the intrinsic behaviour of MMFs, and does not depend on training datasets. Finally, the proposed method allows to improve the peak to background ratio of the acquired signal.


The technology is protected by a pending US patent application and a pending European patent application and is available for licensing. Suitable commercial partners are sought for further development and commercialisation.

The Science

The proposed technology is based on the discovery of a pseudo-linear relationship between the input and output light intensities carried by MMFs. Specifically, such a relationship can be approximated using only real-valued transmission constants, measured detecting the input and output signals carried by MMFs under predetermined spatial modulation patterns, without the need of measuring both the amplitude and phase of the signal.

The technology allows also to increase the peak to background ratio by using spatial modulation patterns that switch on group of light sources associated to the highest real number transmission constants and switch off light sources having lower valued real number transmission constants.

Figure 1: (a) Schematic illustration of the photoacoustic endomicroscopy system; (b) Example 3D photoacoustic endomicroscopy image of mouse red blood cells.

Figure 2: The process of retrieving an input signal (letters ‘KCL’) from the corresponding speckle pattern outputted from MMFs with the real-valued intensity transmission matrix (RVITM) calculated according to the proposed method.


IP Status

WO 2021 144 588 A1 – PCT application (entered US and EP phase)


Further Information

Zhao T. et al. (2022), "Ultrathin, high-speed, all-optical photoacoustic endomicroscopy probe for guiding minimally invasive surgery", arXiv:2205.03122v1, doi:10.48550/arXiv.2205.03122.

Zhao T, et al, (2022). “Video-rate dual-modal photoacoustic and fluorescence imaging through a multimode fibre towards forward-viewing endomicroscopy”, Photoacoustics: 25, 100323, doi:10.1016/j.pacs.2021.100323.

Zhao, T., et al. (2020). “Seeing through multimode fibers with real-valued intensity transmission matrices”. Optics Express: 28, 20978, doi:10.1364/OE.396734



Patent Information:
For Information, Contact:
Lorenza Grechy
King's College London
Wenfeng Xia
Sebastien Ourselin
Tianrui Zhao
Tom Vercauteren