Nalini Singh

Postdoc @UCBerkeley working on machine learning for inverse imaging problems.

[Nalini Singh @nalinimsingh]

1/ New preprint: deep learning MRI motion correction consistent with the acquired data! https://t.co/hl8JtsldTv

Code: https://t.co/DnmREh9Crb

w/@neeldey, @mh3936, Bruce Fischl, Elfar Adalsteinsson, Rob Frost, @AdrianDalca, Polina Golland
@MIT_CSAIL @MGHMartinos @FreeSurferMRI

[Nalini Singh @nalinimsingh]

New paper led by @weiserjpaul using our joint frequency/image space neural network layers for magnetic resonance spectroscopic image reconstruction

[MIT Jameel Clinic for AI & Health @AIHealthMIT]

A team of researchers including #JameelClinic PI @GollandPolina have built a deep learning model called Deep-ER that makes MRSI reconstruction 600x faster than conventional methods, making it easier to map neurological diseases like brain cancer. https://t.co/pL8z2f24Sv

[MIT Jameel Clinic for AI & Health @AIHealthMIT]

Sometimes less is more. #JameelClinic PI @david_sontag is the senior author of a new commentary in @NatMachIntell that suggests that simpler models may be more effective than scBERT in certain scenarios when it comes to single-cell research. Paper: https://t.co/oGbVY6V4Ka

[Nalini Singh @nalinimsingh]

@andrew_ilyas @aleks_madry @KonstDaskalakis That's awesome, congrats!!!

[Guanghan Meng @guanghan_meng]

My lab, Visionary Optical Imaging Lab (VOILA!), applies methods of optical physics and modern computational science to develop cutting-edge optical microscopy technologies for eye and brain imaging. We are hiring - please visit my lab website https://t.co/I3BZIgHCMn for details!

[Ruiming Cao @rmcao_]

Neural space-time model (NSTM) was published this week in @naturemethods !

Check it out: https://t.co/u4OmXGNDi4

It is a flexible and robust model to tackle motion blur and improve temporal resolution in computational cameras/microscopes.🧵👇

[Nalini Singh @nalinimsingh]

@rohitrango Maybe MR reconstruction? Depending on the acquisition pattern, you have to correct global aliasing artifacts of varying severity in image-space -- e.g. the 8x TV-regularized reconstruction in Fig 10: https://t.co/R64oxihNSN

[Mazdak Abulnaga @MazAbulnaga]

Happy to share our latest work on shape-aware segmentation has been accepted to @MELBAJournal! In this work, we tackle the challenging problem of segmenting placental volumes in whole-uterus BOLD MRI Time Series.

[Juan Eugenio Iglesias @JuanEugenioIgl1]

New preprint on Fully Convolutional Slice-to-Volume Reconstruction for Single-Stack MRI
https://t.co/9q6mhraiTq
Following recent single-view depth estimation methods, it produces SOTA reconstructions even with extreme inter-slice motion, eg fetal MR
Work spearheaded by Sean Young

[Rebecca Boiarsky @RBoiarsky]

Sharing a link to my #MLCB2023 oral presentation, since there were some audio issues on the livestream. https://t.co/Bwu6KH2taS. Thanks to the organizers for a fantastic conference!

[Nalini Singh @nalinimsingh]

Some updates: I defended my thesis and started a postdoc at Berkeley with @optrickster.

I'll spend the next few years learning about a wide range of imaging techniques and algorithms for inverse problems -- please reach out if you'd like to talk!

[Rebecca Boiarsky @RBoiarsky]

(1/6) Our deep dive into single cell foundation models, scBERT and scGPT - now on bioRxiv! https://t.co/HK8Lhzn5s6 w/ @nalinimsingh @abuen_dia @david_sontag @gaddyg

[Monica Agrawal @MonicaNAgrawal]

I’m recruiting PhD students @Duke for fall 2024! Consider applying if you’re interested in reimagining healthcare by developing novel ML/NLP methodology. I can advise students through the CS dept and the Biostats & Bioinformatics dept.

Info here: https://t.co/NeqZeNUISF

[Julia Schnabel @ja_schnabel]

@Efrat_Shimron @khammernik @DanielRueckert @BMRRgroup @spieker_vj @hannah_eichhorn Very happy to report that this comprehensive review on deep learning for retrospective motion
correction in MRI by @spieker_vj and @hannah_eichhorn @HelmholtzIml @HelmholtzMunich has been accepted by @IEEE_TMI !

For early access please visit: https://t.co/GDkAZWcNt7

[Nalini Singh @nalinimsingh]

@harini824 @BrownCSDept Awesome, congrats!!!

[Daniel Moyer @dc_moyer]

MedNeurIPS returns for 2023!

https://t.co/PPMosvoyqV

Consider joining us for a day at the intersection of Machine Learning and Medical Imaging, again in the NeurIPS workshops. Submissions due Sept. 29.

[MIT Jameel Clinic for AI & Health @AIHealthMIT]

There's now a plethora of free AI tools online that can sharpen blurry photos 📸 but what about 3D images? @nalinimsingh spoke w/ MIT News about the beauty of combining deep learning + physics when it comes to motion correction in MRI scans. https://t.co/vf5f4IZE2g

[Nalini Singh @nalinimsingh]

@SandyaPhD @UCJointCPH Congrats! :)

[Nalini Singh @nalinimsingh]

Excited for @midl_conference this week! I'm presenting two projects:

Data Consistent Deep Rigid MRI Motion Correction: Tuesday Neuroimaging Oral (9-10:15 AM) + Poster T03

Joint Frequency and Image Space Learning for MRI Reconstruction and Analysis: Wednesday Poster W45

[Adrian Dalca @AdrianDalca]

@SCzolbe is presenting at #CVPR2023 today (TUE-PM-200 in person)

Neuralizer: General Neuroimage Analysis without Re-Training

code: https://t.co/NRq67o2Z5o
video: https://t.co/pxF4IG5Kh0

@FreeSurferMRI @MGHMartinos @mit_caml @MIT_CSAIL @MITEECS @CVPR