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Mikhail A Teverovskiy

from Stamford, CT
Age ~65
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Also known as:
Mikhael A Teverovskiy, Mikhail Teverovskaya, Makhail Teverovskiy, Mikhail Teverosky, Michael M Teverovskaya, Mikhail Y, E Y
Phone and address:
100 Willowbrook Ave APT 7, Stamford, CT 06902
Related to:
Bela Teverovskaya, 83Konstantin Teverovskiy, 30Maria Teverovskaya, 62Anatoliy Teverovskiy, 89
Connected to:
Anabella R Teverovsky, 47Jill S Teverow, 38Frances S Tevers, 74April M Teves, 52Betty S Teves, 80Chris C Teves, 37Dawn M Teves, 53Dwight D Teves, 73Erica L Teves, 36Fernando B Teves, 110

Mikhail Teverovskiy Phones & Addresses

  • 100 Willowbrook Ave APT 7, Stamford, CT 06902
  • 14 Nosband Ave APT 4C, White Plains, NY 10605
  • 190A Osborne Rd, Harrison, NY 10528
  • 24018 Silsby Rd, Beachwood, OH 44122 (216) 381-5631
  • South Euclid, OH

Skills

Bioinformatics • Pattern Recognition • Machine Learning • Image Analysis • Artificial Intelligence • R&D • Algorithms • Medical Imaging • Image Processing • Lifesciences • Signal Processing • Computer Vision • Biotechnology • Cancer • Biomarkers • Genomics • Hardware Diagnostics • Science • Immunohistochemistry • Cell • Statistics • Digital Imaging • Molecular Biology • Commercialization • Clinical Research • Biomedical Engineering • Biochemistry • Oncology • Medical Devices • Cell Biology • Genetics • Life Sciences

Languages

Russian

Industries

Research

Resumes

Resumes

Mikhail Teverovskiy Photo 1

Mikhail Teverovskiy

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Location:
New York, NY
Industry:
Research
Skills:
Bioinformatics
Pattern Recognition
Machine Learning
Image Analysis
Artificial Intelligence
R&D
Algorithms
Medical Imaging
Image Processing
Lifesciences
Signal Processing
Computer Vision
Biotechnology
Cancer
Biomarkers
Genomics
Hardware Diagnostics
Science
Immunohistochemistry
Cell
Statistics
Digital Imaging
Molecular Biology
Commercialization
Clinical Research
Biomedical Engineering
Biochemistry
Oncology
Medical Devices
Cell Biology
Genetics
Life Sciences
Languages:
Russian

Business Records

Name / Title
Company / Classification
Phones & Addresses
Mikhail Teverovskiy
Vice-President
Image Signal R and D Consulting, Inc
Computer Systems Design
1440 Rockside Rd, Cleveland, OH 44134

Publications

Us Patents

Systems And Methods For Treating, Diagnosing And Predicting The Occurrence Of A Medical Condition

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US Patent:
7467119, Dec 16, 2008
Filed:
Mar 14, 2005
Appl. No.:
11/080360
Inventors:
Olivier Saidi - Greenwich CT, US
David A. Verbel - New York NY, US
Mikhail Teverovskiy - Harrison NY, US
Assignee:
Aureon Laboratories, Inc. - Yonkers NY
International Classification:
G06E 1/00
G06E 3/00
G06F 15/18
G06G 7/00
US Classification:
706 21, 600407
Abstract:
Methods and systems are provided that use clinical information, molecular information and computer-generated morphometric information in a predictive model for predicting the occurrence (e. g. , recurrence) of a medical condition, for example, cancer.

Pathological Tissue Mapping

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US Patent:
7483554, Jan 27, 2009
Filed:
Nov 17, 2004
Appl. No.:
10/991897
Inventors:
Angeliki Kotsianti - New York NY, US
Olivier Saidi - Greenwich CT, US
Mikhail Teverovskiy - Harrison NY, US
Assignee:
Aureon Laboratories, Inc. - Yonkers NY
International Classification:
G06K 9/00
C12N 15/07
US Classification:
382128, 382224, 435451
Abstract:
Embodiments of the present invention are directed to quantitative analysis of tissues enabling the measurement of objects and parameters of objects found in images of tissues including perimeter, area, and other metrics of such objects. Measurement results may be input into a relational database where they can be statistically analyzed and compared across studies. The measurement results may be used to create a pathological tissue map of a tissue image, to allow a pathologist to determine a pathological condition of the imaged tissue more quickly.

Systems And Methods For Automated Diagnosis And Grading Of Tissue Images

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US Patent:
7761240, Jul 20, 2010
Filed:
Aug 9, 2005
Appl. No.:
11/200758
Inventors:
Olivier Saidi - Greenwich CT, US
Ali Tabesh - Tucson AZ, US
Mikhail Teverovskiy - Harrison NY, US
Assignee:
Aureon Laboratories, Inc. - Yonkers NY
International Classification:
G06F 19/00
G06K 9/00
G06K 9/20
G06K 9/36
US Classification:
702 19, 382128, 382282, 382286
Abstract:
Systems and methods are provided for automated diagnosis and grading of tissue images based on morphometric data extracted from the images by a computer. The morphometric data may include image-level morphometric data such as fractal dimension data, fractal code data, wavelet data, and/or color channel histogram data. The morphometric data may also include object-level morphometric data such as color, structural, and/or textural properties of segmented image objects (e. g. , stroma, nuclei, red blood cells, etc. ).

Systems And Methods For Treating, Diagnosing And Predicting The Occurence Of A Medical Condition

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US Patent:
20070099219, May 3, 2007
Filed:
Oct 13, 2006
Appl. No.:
11/581052
Inventors:
Mikhail Teverovskiy - Harrison NY, US
David Verbel - New York NY, US
Olivier Saidi - Greenwich CT, US
Assignee:
Aureon Laboratories, Inc. - Yonkers NY
International Classification:
C12Q 1/68
G01N 33/574
G06F 19/00
US Classification:
435006000, 435007230, 702019000
Abstract:
Methods and systems are provided that use clinical information, molecular information and computer-generated morphometric information in a predictive model for predicting the occurrence (e.g., recurrence) of a medical condition, for example, cancer. In an embodiment, a model that predicts prostate cancer recurrence is provided, where the model is based on features including seminal vesicle involvement, surgical margin involvement, lymph node status, androgen receptor (AR) staining index of tumor, a morphometric measurement of epithelial nuclei, and at least one morphometric measurement of stroma. In another embodiment, a model that predicts clinical failure post prostatectomy is provided, wherein the model is based on features including biopsy Gleason score, lymph node involvement, prostatectomy Gleason score, a morphometric measurement of epithelial cytoplasm, a morphometric measurement of epithelial nuclei, a morphometric measurement of stroma, and intensity of androgen receptor (AR) in racemase (AMACR)-positive epithelial cells.

Pathological Tissue Mapping

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US Patent:
20090262993, Oct 22, 2009
Filed:
Nov 14, 2008
Appl. No.:
12/313015
Inventors:
Angeliki Kotsianti - New York NY, US
Olivier Saidi - Greenwich CT, US
Mikhail Teverovskiy - Harrison NY, US
Assignee:
Aureon Laboratories, Inc. - Yonkers NY
International Classification:
G06K 9/00
US Classification:
382128
Abstract:
Embodiments of the present invention are directed to quantitative analysis of tissues enabling the measurement of objects and parameters of objects found in images of tissues including perimeter, area, and other metrics of such objects. Measurement results may be input into a relational database where they can be statistically analyzed and compared across studies. The measurement results may be used to create a pathological tissue map of a tissue image, to allow a pathologist to determine a pathological condition of the imaged tissue more quickly.

Systems And Methods For Treating Diagnosing And Predicting The Occurrence Of A Medical Condition

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US Patent:
20100088264, Apr 8, 2010
Filed:
Apr 7, 2008
Appl. No.:
12/449710
Inventors:
Mikhail Teverovskiy - Harrison NY, US
David A. Verbel - New York NY, US
Olivier Saidi - Greenwich CT, US
Assignee:
Aureon Laboratories Inc. - Yonkers NY
International Classification:
G06N 5/02
US Classification:
706 46
Abstract:
Methods and systems are provided that use clinical information, molecular information and computer-generated morphometric information in a predictive model for predicting the occurrence (e.g., recurrence) of a medical condition, for example, cancer. In an embodiment, a model that predicts prostate cancer recurrence is provided, where the model is based on features including one or more (e.g., all) of biopsy Gleason score, seminal vesicle invasion, extracapsular extension, preoperative PSA, dominant prostatectomy Gleason grade, the relative area of AR+ epithelial nuclei, a morphometric measurement of epithelial nuclei, and a morphometric measurement of epithelial cytoplasm. In another embodiment, a model that predicts clinical failure post-prostatectomy is provided, wherein the model is based on features including one or more (e.g., all) of dominant prostatectomy Gleason grade, lymph node invasion status, one or more morphometric measurements of lumen, a morphometric measurement of cytoplasm, and average intensity of AR in AR+/AMACR− epithelial nuclei.

Comparative Cancer Survival Models To Assist Physicians To Choose Optimal Treatment

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US Patent:
20200058125, Feb 20, 2020
Filed:
Aug 14, 2018
Appl. No.:
15/998481
Inventors:
Mikhail Teverovskiy - Stamford CT, US
International Classification:
G06T 7/00
G06T 7/11
G06T 7/194
G16H 50/30
G16H 50/50
Abstract:
A computer implemented method and a system choosing optimal disease treatment among several possible treatment options for a patient are provided. The system computes cancer-free survival rates for each considered treatment based on predicting recurrence rate of a disease and/or cancer outcome for a particular patient. The treatment survival models use quantitative data from histopathological images of the patient, clinical data and other patient information. The system segments the histopathological images into biologically meaningful components; automatically determines disease-affected regions in one or more of the segmented image components. The system also partitions the disease-affected regions in each image into a number clusters. Those that are determined to be the most associated with the disease outcome are used as a source of the imaging information for the survival modeling. Optimal treatment is suggested as the treatment with probability of the cancer free survival within a certain time period is maximized.

Iris Recognition Systems And Methods Of Using A Statistical Model Of An Iris For Authentication

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US Patent:
20170337424, Nov 23, 2017
Filed:
May 17, 2017
Appl. No.:
15/597927
Inventors:
- New York NY, US
Mikhail Teverovskiy - White Plains NY, US
Assignee:
EyeLock LLC - New York NY
International Classification:
G06K 9/00
G06K 9/40
Abstract:
The present disclosure describes systems and methods of using iris data for authentication. A biometric encoder may translate an image of the iris into a rectangular representation of the iris. The rectangular representation may include a plurality of rows corresponding to a plurality of annular portions of the iris. The biometric encoder may extract an intensity profile from at least one of the plurality of rows, the intensity profile modeled as a stochastic process. The biometric encoder may obtain a stationary stochastic component of the intensity profile by removing a non-stationary stochastic component from the intensity profile. The biometric encoder may remove at least a noise component from the stationary component using auto-regressive based modeling, to produce at least a non-linear background signal, and may combine the non-stationary component and the at least the non-linear background signal, to produce a biometric template for authenticating the person.
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Mikhail A Teverovskiy from Stamford, CT, age ~65 Get Report