Evading scientific stalemates

This week I have been thinking about a strange thing that happened in my research group. One day while I was doing my MSc, me and my colleagues we were discussing some lab results. A small change on our experimental setup provided much better images than the ones we were getting up to that point. This change, even though small, was puzzling at first. It was counter-intuitive. We quickly realized why it was improving our measurements. However, this was not the important thing. By doing that small change, our system, which at the time was just simply an imaging system, seemed to be able to tackle much more difficult experimental scenarios. We thought that we had discovered a new property of the systems we were developing. We were right.

After that initial idea, we quickly designed some experiments to verify our initial guesses. Everything seemed to work, but we were not 100% sure why. We had some general ideas, some intuitions. Our plan was to keep doing some experiments while we figured all the details. We published some papers and started thinking big. This approach could be applied to real scenarios. We started collaborating with some other groups and in the end we developed a real-life system in collaboration with them. That was published in a very good journal.

However, even though we figured out the bugging details we had at the beginning, we were never able to build a model that allowed us to predict or at least to conjecture about what could be the limits of our technique.

Fast forward ~3 years to today. We have a meeting planned for next week to discuss why our latest experiments are not providing the results we expected. After months of PhD (and MSc) students work, we are at a stalemate. Some days it seems that we are close to change something in the lab that will yield the expected improvement. Some days, after hundreds of trials, everything remains the same. Given the lack of a physical model to hold to, the group is searching with a blindfold, and I don’t think this is working at all.

If I had to make a prediction right now, I would say that the research line is dead (long live the research line!). It shouldn’t be dramatic, it is just science (sometimes it works, sometimes it doesn’t). However, during all this process, several students joined the group and started their MSc’s and PhD’s on the topic. This could be dramatic for them. During all this time, I have been working in quite a lot of different stuff. I missed some publications, which hurt my CV. However, when something did not work, I always had different stuff to try. I think I have a wider scope of my field because of that. In the end, I have published more than enough to write my thesis.

I guess that’s a good practice: never put all your eggs in the same basket. You need to have hundreds of ideas to get a good one. Take your time to explore them, and build strong foundations where new people can construct upon without fear of falling down.

Weekly recap (29/04/2018)

This week we have a lot of interesting stuff:

Observing the cell in its native state: Imaging subcellular dynamics in multicellular organisms

Adaptive Optics + Light Sheet Microscopy to see living cells inside the body of a Zebra fish (the favorite fish of biologists!). Really impressive images overcoming scattering caused by tissue. You can read more about the paper on Nature and/or Howard Hughes Medical Institute.

 


The Feynmann Lectures on Physics online

I just read on OpenCulture that The Feynmann Lectures on Physics have been made available online. Until now, only the first part was published, but now you can also find volumes 2 and 3. Time to reread the classics…


Imaging Without Lenses

An interesting text appeared this week in American Scientist covering some aspects of the coming symbiosis between optics, computation and electronics. We are already able to overcome optical resolution, obtain phase information, or even imaging without using traditional optical elements, such as lenses. What’s coming next?


All-Optical Machine Learning Using Diffractive Deep Neural Networks

A very nice paper appeared on arXiv this week.

Xing Lin, Yair Rivenson, Nezih T. Yardimci, Muhammed Veli, Mona Jarrahi, Aydogan Ozcan

We introduce an all-optical Diffractive Deep Neural Network (D2NN) architecture that can learn to implement various functions after deep learning-based design of passive diffractive layers that work collectively. We experimentally demonstrated the success of this framework by creating 3D-printed D2NNs that learned to implement handwritten digit classification and the function of an imaging lens at terahertz spectrum. With the existing plethora of 3D-printing and other lithographic fabrication methods as well as spatial-light-modulators, this all-optical deep learning framework can perform, at the speed of light, various complex functions that computer-based neural networks can implement, and will find applications in all-optical image analysis, feature detection and object classification, also enabling new camera designs and optical components that can learn to perform unique tasks using D2NNs.

Imagine if Fourier Transforms were discovered before lenses, and then some day someone comes up with just a piece of glass and says “this can make the computations of FT at the speed of light”. Very cool read.


OPEN SPIN MICROSCOPY

I just stumbled upon this project while reading Lab on the Cheap. Seems like a very good resource if you plan to build a light-sheet microscope and do not wanna spend $$$$ on Thorlabs.


Artificial Inteligence kits from Google, updated edition

Last year, AIY Projects launched to give makers the power to build AI into their projects with two do-it-yourself kits. We’re seeing continued demand for the kits, especially from the STEM audience where parents and teachers alike have found the products to be great tools for the classroom. The changing nature of work in the future means students may have jobs that haven’t yet been imagined, and we know that computer science skills, like analytical thinking and creative problem solving, will be crucial.

We’re taking the first of many steps to help educators integrate AIY into STEM lesson plans and help prepare students for the challenges of the future by launching a new version of our AIY kits. The Voice Kit lets you build a voice controlled speaker, while the Vision Kit lets you build a camera that learns to recognize people and objects (check it out here). The new kits make getting started a little easier with clearer instructions, a new app and all the parts in one box.

To make setup easier, both kits have been redesigned to work with the new Raspberry Pi Zero WH, which comes included in the box, along with the USB connector cable and pre-provisioned SD card. Now users no longer need to download the software image and can get running faster. The updated AIY Vision Kit v1.1 also includes the Raspberry Pi Camera v2.

Looking forward to see the price tag and the date they become available.

The week in papers (22/04/18)

As a way to keep posts going, I am starting a short recap about interesting papers being published (or being discovered) every now and then. Probably I will write longer posts about some of them in the future.

Let’s get this thing going:

Two papers using ‘centroid estimation‘ to retrieve interesting information:

Extract voice information using high-speed camera

Mariko AkutsuYasuhiro Oikawa, and Yoshio Yamasaki, at The Journal of the Acoustical Society of America

Kilohertz binary phase modulator for pulsed laser sources using a digital micromirror device

People at Judkewitz lab tend to do really cool stuff. This time they have implemented a binary phase modulator using a DMD.

Kilohertz binary phase modulator for pulsed laser sources using a digital micromirror device,

M. Hoffmann et al, at Optics Letters

Abstract:

The controlled modulation of an optical wavefront is required for aberration correction, digital phase conjugation, or patterned photostimulation. For most of these applications, it is desirable to control the wavefront modulation at the highest rates possible. The digital micromirror device (DMD) presents a cost-effective solution to achieve high-speed modulation and often exceeds the speed of the more conventional liquid crystal spatial light modulator but is inherently an amplitude modulator. Furthermore, spatial dispersion caused by DMD diffraction complicates its use with pulsed laser sources, such as those used in nonlinear microscopy. Here we introduce a DMD-based optical design that overcomes these limitations and achieves dispersion-free high-speed binary phase modulation. We show that this phase modulation can be used to switch through binary phase patterns at the rate of 20 kHz in two-photon excitation fluorescence applications.

Controlling phase is of paramount interest in multiple optical scenarios. Doing it fast is very difficult, given that spatial light modulators that are really good at modulating phase precisely tend to be slow (~hundreds of Hz). On the other side, intensity modulators such as DMDs are very fast (~20 kHz), but they cannot directly modulate phase. There have been several workarounds with the general idea of using DMDs to modulate phase. I remember a very nice paper by A. Mosk, using groups of mirrors to codify the phase of a superpixel.

Here, they use the fact that DMDs reflect light in two different directions to introduce a phase shift with a moving mirror into one of the reflection directions, achieving binary phase distributions at kHz refresh rates.

 

 

Seems like we are getting closer and closer to get a high-efficiency method to modulate phase with DMD’s.

Light transport and imaging through complex media & Photonics West 2018

Last ~20 days have been completely crazy. First, I went to a meeting organized by the Royal Society: Light transport and imaging through complex media. It was amazing. Beautiful place, incredible researchers, and a nice combination of signal processing and optical imaging. I am sure I will be looking for future editions.

After that, I assisted Photonics West. Both BIOS and OPTO were full of interesting talks. Scattering media, adaptive optics, DMDs, some compressive sensing… Fantastic week. There I talked about two recent works we made in Spain: balanced photodetection single-pixel imaging and phase imaging using a DMD and a lateral position detector. Both contributions were very well received, and I am happy with the feedback I got. So many new ideas… now I need some time to implement them! I plan on writing a bit here on the blog about the last work, which has been published in the last issue of Optica.

 

Some of the cool stuff I heard about:

Valentina Emiliani – Optical manipulation of neuronal circuits by optical wave front shaping. Very cool implementations combining multiple SLMs and temporal focusing to see how neurons work.

Richard Baraniuk – Phase retrieval: tradeoffs and a new algorithm. How to recover phase information from intensity measurements. Compressive sensing and inverse problems. Very interesting, and a really good speaker. It is difficult to find someone capable of explaining these concepts as easily as Richard.

Michael Unser – GlobalBioIm

When being confronted with a new imaging problem, the common experience is that one has to reimplement (if not reinvent) the wheel (=forward model + optimization algorithm), which is very time consuming and also acts as a deterrent for engaging in new developments. This Matlab library aims at simplifying this process by decomposing the workflow onto smaller modules, including many reusable ones since several aspects such as regularization and the injection of prior knowledge are rather generic. It also capitalizes on the strong commonalities between the various image formation models that can be exploited to obtain fast, streamlined implementations.

Oliver Pust – High spatial resolution hyperspectral camera based on a continously variable filter. Really cool concept of merging a continous filter and multiple expositions to obtain hyperspectral information and even 3D images.

Seungwoo Shin – Exploiting a digital micromirror device for a multimodal approach combinning optical diffraction tomography and 3D structured illumination microscopy. I am always happy to see cool implementations with DMDs. This is one of them. KAIST delivers.

We propose a multimodal system combining ODT and 3-D SIM to measure both 3-D RI and fluorescence distributions of samples with advantages including high spatiotemporal resolution as well as molecular specificity. By exploiting active illumination control of a digital micromirror device and two different illumination wavelengths, our setup allows to individually operate either ODT or 3-D SIM. To demonstrate the feasibility of our method, 3-D RI and fluorescence distributions of a planar cluster of fluorescent beads were reconstructed. To further demonstrate the applicability, a 3-D fluorescence and time-lapse 3-D RI distributions of fluorescent beads inside a HeLa cell were measured.

Post featured image extracted from here.

Optical companding

Christmas came and gone, and I am still trying to keep up with some papers I’ve read in the last months.

The guys at UCLA keep doing impressive stuff. First time I saw something from them was their work on Nature about ultrafast optical imaging (woah!).

This time they have proposed a way to improve the digitization of an electrical signal. Living in the time of the ‘great convergence’, every time we are more aware than Optics, Electronics, and Computer Science are closely related. Nowadays, in order to acquire optical information, one has almost always to deal with electrical signals in the analog domain, which need to be digitized before working with them in a computer. To do so, the most used tools are analog-to-digital converters (ADC). These instruments receive an electrical signal (analog), and convert it to a digital signal (a number representing the voltage or the current you are working with). This quantification sometimes results problematic, given that the full dynamic range of the signal (from the maximum to the minimum value) has to be divided in a finite number of steps (bins). If the signal presents very low variations, the bins might be not small enough to see the full details. One can try to see those details by amplifying the signal, but then the bigger values of the signal might be larger than the maximum value measurable by the ADC, provoking saturation.

Jalali’s group proposes to use Optical Companding to overcome this issue. The fundamental idea is to use optical processes that are not linear to compress the high amplitude signal parts, while amplifying the small amplitude signal values at the same time. After that, a traditional ADC digitizes the signal, and the knowledge about the optical compressor makes it possible to restore the original signal with great accuracy.

Optical Companding,

Yunshan Jiang, Bahram Jalali, submitted on 29 Dec 2017, https://arxiv.org/abs/1801.00007

(featured image exctracted from Fig. 1 of the manuscript)

Abstract,
We introduce a new nonlinear analog optical computing concept that compresses the signal’s dynamic range and realizes non-uniform quantization that reshapes and improves the signal-to-noise ratio in the digital domain.