Lee Kamentsky

Broad Institute of MIT and Harvard · Imaging Platform

Understanding cellular architectures and their connectivity is essential for interrogating system function and dysfunction. However, we lack technologies for mapping the multiscale details of individual cells and their connectivity in the human organ–scale system. We developed a platform that simultaneously extracts spatial, molecular, morphologica...

As advances in microscopy imaging provide an ever clearer window into the human brain, accurate reconstruction of neural connectivity can yield valuable insight into the relationship between brain structure and function. However, human manual tracing is a slow and laborious task, and requires domain expertise. Automated methods are thus needed to e...

Neuronal ensembles that hold specific memory (memory engrams) have been identified in the hippocampus, amygdala, or cortex. However, it has been hypothesized that engrams of a specific memory are distributed among multiple brain regions that are functionally connected, referred to as a unified engram complex. Here, we report a partial map of the en...

For large-scale vision tasks in biomedical images, the labeled data is often limited to train effective deep models. Active learning is a common solution, where a query suggestion method selects representative unlabeled samples for annotation, and the new labels are used to improve the base model. However, most query suggestion models optimize thei...

Synaptic connectivity detection is a critical task for neural reconstruction from Electron Microscopy (EM) data. Most of the existing algorithms for synapse detection do not identify the cleft location and direction of connectivity simultaneously. The few methods that computes direction along with contact location have only been demonstrated to wor...

Synaptic connectivity detection is a critical task for neural reconstruction from Electron Microscopy (EM) data. Most of the existing algorithms for synapse detection do not identify the cleft location and direction of connectivity simultaneously. The few methods that computes direction along with contact location have only been demonstrated to wor...

CellProfiler has enabled the scientific research community to create flexible, modular image analysis pipelines since its release in 2005. Here, we describe CellProfiler 3.0, a new version of the software supporting both whole-volume and plane-wise analysis of three-dimensional (3D) image stacks, increasingly common in biomedical research. CellProf...

Modules with support for 3D in CellProfiler. Overview of modules available in CellProfiler 3.1.0 for 3D image analysis. 3D, three-dimensional. (TIF)

Code to asses per-object segmentation accuracy in CellProfiler and MorphoLibJ. A file to reproduce the results presented in S6 Fig. This contains the ground truth images, CellProfiler-produced segmentations, and MorphoLibJ-produced segmentations, as well as a Jupyter notebook that can be run from the directory once unzipped to replicate the code. (...

Segmentation steps for the analysis of synthetic images depicting HL60 cell line nuclei. Images are available from the Broad Bioimage Benchmark Collection (https://data.broadinstitute.org/bbbc/BBBC024/), as in Fig 2C of the main paper. Synthetic images with 75% clustering probability and low SNR were chosen for analysis. The data set was generated...

Segmentation steps for the analysis of synthetic images from the cell tracking challenge (http://www.celltrackingchallenge.net) depicting HL60 cell line nuclei. Images are taken from the Broad Bioimage Benchmark Collection (https://data.broadinstitute.org/bbbc/BBBC035/), as in Fig 2D of the main paper. (A) Original 3D image of HL60 nuclei prior to...

Example pipeline and nuclei image for deep learning in CellProfiler 3.0. Example pipeline and image needed to run the ClassifyPixels-Unet module. (ZIP)

Segmentation steps for the analysis of mouse embryo blastocyst nuclei stained with Hoechst. Images are available from the Broad Bioimage Benchmark Collection (https://data.broadinstitute.org/bbbc/BBBC032/), as in Fig 2A of the main paper. (A) Original 3D image of blastocyst nuclei prior to analysis. (B) Evaluation of CellProfiler 3.0 performance in...

Distributed-CellProfiler enables processing thousands of images in parallel. A data set of seventeen 384-well plates was processed using Distributed-CellProfiler on an AWS cluster. Each plate comprised 3,456 five-channel images (2,160 × 2,160 pixels). A CellProfiler pipeline was run on each image to identify cells and then extract measurements per...

Comparison of runtimes between CellProfiler 3.0 and CellProfiler 2.2. (Toward the left: CellProfiler 3.0 is faster; toward the right: CellProfiler 2.2 is faster). We compared the performance of example pipelines (available at https://github.com/CellProfiler/examples and http://cellprofiler.org) for CellProfiler 2.2 and 3.0 on OS X 10.12.6 (2.8 GHz...

Fiji macros used for each file. Macro code constructed in the MorphoLibJ plugin for Fiji software that was used for analysis of 3D image examples presented in Fig 1 and S2–S5 Figs. (XLSX)

Image segmentation speed comparison of CellProfiler and the MorphoLibJ 1.3.3 plugin in Fiji (ImageJ 1.51n) on x-64 PC (Dell 7280) Windows 10 Pro (2.8 GHz Intel Core i7-7600U CPU and 16 GB 2133 MHz DDR4 SDRAM). Units of time are in seconds. One image representing the 72-hour time point (72 hours) was used to compare CellProfiler 3.0 and Fiji present...

CellProfiler measurements of mouse blastocysts. Measurements of mouse blastocyst cells and GAPDH transcript foci created by CellProfiler; these serve as the underlying data for Fig 3F. GAPDH, glyceraldehyde 3-phosphate dehydrogenase. (XLSX)

CellProfiler measurements of hiPSCs. Per cell measurements of hiPSCs created by CellProfiler; these serve as the underlying data for Fig 4D. hiPSC, human induced pluripotent stem cell. (XLSX)

Example pipelines and configuration files needed to run CellProfiler on AWS. These pipelines and files can be used to run Distributed-CellProfiler; they are specifically configured to run the Cell Painting assay [7]. AWS, Amazon Web Services. (ZIP)

Segmentation steps for the analysis of mouse trophoblast stem cell nuclei stained with Hoechst. Images are available from the Broad Bioimage Benchmark Collection (https://data.broadinstitute.org/bbbc/BBBC033/), as in Fig 2B of the main paper. (A) Original 3D stem cell nuclei image prior to analysis. (B) Evaluation of CellProfiler 3.0 performance in...

Accuracy of nuclear segmentation using CellProfiler and MorphoLibJ. The fraction of nuclei correctly identified relative to their ground truth was assessed for both CellProfiler (solid line) and MorphoLibJ (dashed line) for the results shown in Fig 1 and S2–S5 Figs. A nucleus was considered correctly segmented at a given threshold if the intersecti...

Segmentation of U2OS cells in images, using the deep learning based ClassifyPixels-Unet plugin. Image is available from the Broad Bioimage Benchmark Collection (https://data.broadinstitute.org/bbbc/BBBC022/, filename XMtest_B12_s2_w19F7E0279-D087-4B5E-9899-61971C29CB78.tif, see S4 File). The U-Net model was trained using 150 manually annotated DAPI...

CellProfiler 3D module run times. CPU and wall-clock runtimes for individual CellProfiler modules in the example pipelines; the summary of this data can be seen in S2 Table. 3D, three-dimensional; CPU, central processing unit (XLSX)

Imaging flow cytometry (IFC) enables the high throughput collection of morphological and spatial information from hundreds of thousands of single cells. This high content, information rich image data can in theory resolve important biological differences among complex, often heterogeneous biological samples. However, data analysis is often performe...

: Schistosomiasis is a debilitating neglected tropical disease, caused by flatworms of Schistosoma genus. The treatment relies on a single drug, praziquantel (PZQ), making the discovery of new compounds extremely urgent. In this work, we integrated QSAR-based virtual screening (VS) of Schistosoma mansoni thioredoxin glutathione reductase (SmTGR) in...

Schistosomiasis is a neglected tropical disease that affects millions of people worldwide. Thioredoxin glutathione reductase of Schistosoma mansoni (SmTGR) is a validated drug target that plays a crucial role in the redox homeostasis of the parasite. We report the discovery of new chemical scaffolds against S. mansoni using a combi-QSAR approach fo...

Recently, our in silico repositioning-chemogenomics approach predicted paroxetine (PAR), an antidepressant drug, as a inhibitor of Schistosoma mansoni serotonin transporters (SmSERTs), and consequently, a new anti-schistosomal candidate. With the aim of determining the anti-schistosomal activity of this drug, we initially used a spectrophotometric...

Patients with a germline mutation in von Hippel-Lindau (VHL) develop renal cell cancers and hypervascular tumors of the brain, adrenal glands, and pancreas as well as erythrocytosis. These phenotypes are driven by aberrant expression of HIF2α, which induces expression of genes involved in cell proliferation, angiogenesis, and red blood cell product...

CONCLUSIONS: Use of combined urinary testing for TMPRSS2:Erg and PCA3 to determine who should undergo prostate biopsy can avert unnecessary biopsy in 49% of men while retaining 95% sensitivity in detecting aggressive PCa with consequent lifetime cost savings evident among men less than 65 years of age.

Bioimaging software developed in a research setting often is not widely used by the scientific community. We suggest that, to maximize both the public's and researchers' investments, usability should be a more highly valued goal. We describe specific characteristics of usability toward which bioimaging software projects should aim.

We present a toolbox for high-throughput screening of image-based Caenorhabditis elegans phenotypes. The image analysis algorithms measure morphological phenotypes in individual worms and are effective for a variety of assays and imaging systems. This WormToolbox is available through the open-source CellProfiler project and enables objective scorin...

Supplementary Figure 1. Distribution of cluster sizes and performance of untangling. Supplementary Figure 2. Performance of untangling in relation to clusters size, size of training set, and speed. Supplementary Figure 3. Assay 1, part 1: Detection of individual adult worms, in the presence of clustering, eggs and progeny. Supplementary Figure 4. A...

Unlabelled: There is a strong and growing need in the biology research community for accurate, automated image analysis. Here, we describe CellProfiler 2.0, which has been engineered to meet the needs of its growing user base. It is more robust and user friendly, with new algorithms and features to facilitate high-throughput work. ImageJ plugins c...

Multiparameter laser scanning cytometry has been applied to the automatic counting of probe spots and the simultaneous measurement of cellular DNA for fluorescence in situ hybridization (FISH) prepared specimens counterstained with propidium iodide. Relatively low resolution imaging, highly variable probe fluorescence, spectral overlap of probe wit...

To show that laser scanning cytometry (LSCM) can provide data equivalent to flow cytometry (FCM) data and furnish a number of benefits, including cell relocation for visualization and several additional measurement features that may make it more suitable than FCM for pathology laboratories. A laser scanning cytometer, the LSC, was developed. Severa...

We describe a computer-controlled 10 microns spot size laser scanning cytometer for making multiple wavelength fluorescence and scatter measurements of unconstrained cells on a surface such as a microscope slide. Designated areas of slides placed on a microscope stage are automatically scanned, and cells which generate above-threshold scatter or fl...