Indica
Backed by cutting edge technology, an uncompromising focus on ease-of-use and dedicated customer service, Indica Labs’ software and services are being used to make vital discoveries in pathology labs and research organizations around the world.

Tissue Classifier

Tissue Classifier Add-on

 

Product Overview

The Tissue Classifier Add-on utilizes a state-of-the-art machine learning algorithm to identify tissue types based on color, texture, and contextual features.  Utilizing a “learn-by-example” approach, the user highlights a few distinct tissue types and within seconds the software learns to categorize tissue.  The tissue classifier add-on module runs within/ is embedded in the HALO platform and can be used in conjunction with any of our cell-based analysis modules for BF or FL analysis, ultimately minimizing manual outlining of regions of interest.

To learn more, watch this short demonstration below to see how the tissue classifier can be trained to identify tumor regions for subsequent IHC analysis.

The Tissue Classifier Add-on integrates seamlessly into the HALO™ platform which is compatible with a number of file formats.

Contact info@indicalab.com for product demonstration and pricing information or upload some images for a free trial.

Tissue Classifier Add-on

The Tissue Classifier Add-on utilizes a state-of-the-art machine learning algorithm to identify tissue types based on color, texture, and contextual features.  Utilizing a “learn-by-example” approach, the user highlights a few distinct tissue types and within seconds the software learns to categorize tissue.  The tissue classifier add-on module runs within/ is embedded in the HALO platform and can be used in conjunction with any of our cell-based analysis modules for BF or FL analysis, ultimately minimizing manual outlining of regions of interest.

To learn more, watch this short demonstration below to see how the tissue classifier can be trained to identify tumor regions for subsequent IHC analysis.

HALO is compatible with a broad spectrum of image and digital slide formats.  Yours not on the list? Email us your requirements.

Non-proprietary (JPG, TIF)
Nikon (ND2)
3D Histech (MRXS)
Perkin Elmer (QPTIFF, component TIFF)
Olympus (VSI)
Hamamatsu (NDPI, NDPIS)
Aperio (SVS, AFI)
Zeiss (CZI)
Leica (SCN, LIF)
Philips (Requires Philips IMS)

Here are a few publications that cite the use of our HALO Tissue Classifier Add-on. Your publication not on the list?  Drop us an email to let us know about it!

Title Author Year Journal
Bortezomib prevents cytarabine resistance in MCL, which is characterized by down-regulation of dCK and up-regulation of SPIB resulting in high NF-κB activity Freiburghaus C, Emruli VK, Johansson A, Eskelund CW, Grønbæk K, Olsson R, Ek F, Jerkeman M, Ek S 2018 BMC Cancer
Digital image analysis improves precision of PD‐L1 scoring in cutaneous melanoma Koelzer VH, Gisler A, Hanhart JC, Griss J, Wagner SN, Willi N, Cathomas G, Sachs M, Kempf W, Thommen DS, Mertz KD 2018 Histopathology
Digital image analysis of Ki67 proliferation index in breast cancer using virtual dual staining on whole tissue sections: clinical validation and inter‑platform agreement Koopman T, Buikema HJ, Hollema H, de Bock GH, van der Vegt B 2018 Breast Cancer Research and Treatment
Induction of hemangiosarcoma in mice after chronic treatment with S1P-modulator siponimod and its lack of relevance to rat and human Pognan F, Mahl JA, Papoutsi M, David Ledieu D, Raccuglia M, Theil D, Voytek SB, Devine PJ, Kubek‑Luck K, Claudio N, Cordier A, Heier A, Kolly C, Hartmann A, Chibout S-D, Bouchard P, Trendelenburg C 2018 Archives of Toxicology
RAD51 foci as a functional biomarker of homologous recombination repair and PARP inhibitor resistance in germline BRCA mutated breast cancer  Cruz C, Castroviejo-Bermejo M, Gutiérrez-Enríquez S, Llop-Guevara A, Ibrahim YH, Gris-Oliver A, Bonache S, Morancho B, Bruna A, Rueda OM, Lai Z, Polanska UM, Jones GN,Kristel P, de Bustos L, Guzman M, Rodriguez O, Grueso J, Montalban G, Caratú G, Mancuso F, Fasani R, Jiménez J, Howat WJ, Dougherty B, Vivancos A, Nuciforo P, Serres-Créixams X, Rubio IT, Oaknin A, Cadogan O, Barrett JC, Caldas C, Baselga J, Saura C, Cortés J, Arribas J, Jonkers J, Díez O, O’Connor MJ, Balmaña J, SerraV 2018 Annals of Oncology
The novel ATM inhbitior (AZ31) enhances antitumor activity in patient derived xenografts that are resistant to irinotecan montherapy Greene J, Nguyen A, Bagby SM, Jones GN, Tai WM, Quackenbush KS, Schreiber A, Messersmith WA, Devaraj KM, Blatchford P, Eckhardt SG, Cadogan EB, Hughes GD, Smith A, Pitts TM, Arcaroli JJ 2018 Oncotarget
A randomized, open-label study of the efficacy and safety of AZD4547 monotherapy versus paclitaxel for the treatment of advanced gastric adenocarcinoma with FGFR2 polysomy or gene amplification Van Cutsem E, Bang Y-J,  Mansoor W,  Petty RD, Chao Y, Cunningham D, Ferry DR, N. R. Smith NR, Frewer P, Ratnayake J, Stockman PK, Kilgour E, and Landers D 2017 Annals of Oncology
An ancestral retroviral protein identified as a therapeutic target in type-1 diabetes Levet S, Medina J, Joanou J, Demolder A, Queruel N, Réant K, Normand M, Seffals M, Dimier J, Germi R, Piofczyk T, Portoukalian J, Touraine J-L, Perron H 2017 JCI Insight
cFOS-SOX9 Axis Reprograms Bone Marrow-Derived Mesenchymal Stem Cells into Chondroblastic Osteosarcoma He Y, Zhu W, Shin MH, Gary J, Liu C, Dubois W, Hoover SB, Jiang S, Marrogi E, Mock B, Simpson RM, and Huang J 2017 Stem Cell Reports
Identification of the SUMO E3 ligase PIAS1 as a potential survival biomarker in breast cancer Chanda A, Chan A, Deng L, Kornaga EN, Enwere EK, Morris DG, Bonni S 2017 PLOS One
In vivo characterization of a new type of biodegradable starch microsphere for transarterial embolization Sommer CM, Do TD, Schlett CL, Flechsig P, Gockner TL, Kuthning A, Vollherbst DF, Pereira PL, Kauczor HU, Macher-Göppinger S 2017 Journal of Biomaterials Applications
A Phase II Trial of Dovitinib in BCD-Unresponsive Urothelial Carcinoma with FGFR3 Mutations or Over-Expression: Hoosier Cancer Research Network Trial HCRN 12-157 Hahn NH, Bivalacqua TJ, Ross AE, Netto GJ, Baras AS, Park JC, Chapman C, Masterson TA, Koch MO, Bihrle R, Foster RS, Gardner TA, Cheng L, Jones DR, Kyle McElyea K, Sandusky GE, Breen T, Liu Z, Albany C, Moore ML, Loman RA, Reed A, Turner SA, de Abreu FB, Gallagher TL, Tsongalis GJ, Plimack ER, Greenberg RE, Geynisman DM 2016 Clinical Cancer Research
Bimodality of intratumor Ki67 expression is an independent prognostic factor of overall survival in patients with invasive breast carcinoma Laurinavicius A, Plancoulaine B, Rasmusson A, Besusparis J, Augulis R, Meskauskas R, Herlin P, Laurinaviciene A, Muftah AAA, Miligy I, Aleskandarany M, Rakha EA, Green AR, Ellis IO 2016 Virchows Archiv

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