A5091763855- Evolution and Genetic Dynamics
- Medical Image Segmentation Techniques
- AI in cancer detection
- Image and Signal Denoising Methods
- RNA and protein synthesis mechanisms
- Bacteriophages and microbial interactions
- Chromosomal and Genetic Variations
- Radiomics and Machine Learning in Medical Imaging
- Cell Image Analysis Techniques
- Gene Regulatory Network Analysis
- Fractal and DNA sequence analysis
- Digital Radiography and Breast Imaging
- Origins and Evolution of Life
- Genetics, Bioinformatics, and Biomedical Research
- Protein Structure and Dynamics
- Bacterial Genetics and Biotechnology
- Mathematical and Theoretical Epidemiology and Ecology Models
- Agriculture and Biological Studies
- Cerebrospinal fluid and hydrocephalus
- Image Retrieval and Classification Techniques
- Mathematical Biology Tumor Growth
- Various Chemistry Research Topics
- Advanced Neuroimaging Techniques and Applications
- Gene expression and cancer classification
- Plant Genetic and Mutation Studies
IBM Research - Haifa
2021-2023
Johns Hopkins Medicine
2022
University of Haifa
2021-2022
Johns Hopkins University
2022
Stony Brook University
2015-2017
Applied Mathematics (United States)
2015
Technion – Israel Institute of Technology
2007-2013
Institute of Cytology and Genetics
1981-2003
Novosibirsk State University
1999-2003
Biobase (Germany)
2003
Background Digital breast tomosynthesis (DBT) has higher diagnostic accuracy than digital mammography, but interpretation time is substantially longer. Artificial intelligence (AI) could improve reading efficiency. Purpose To evaluate the use of AI to reduce workload by filtering out normal DBT screens. Materials and Methods The retrospective study included 13 306 examinations from 9919 women performed between June 2013 November 2018 two health care networks. cohort was split into training,...
Importance An accurate and robust artificial intelligence (AI) algorithm for detecting cancer in digital breast tomosynthesis (DBT) could significantly improve detection accuracy reduce health care costs worldwide. Objectives To make training evaluation data the development of AI algorithms DBT analysis available, to develop well-defined benchmarks, create publicly available code existing methods. Design, Setting, Participants This diagnostic study is based on a multi-institutional...
Males of a Drosophila melanogaster isogenic line with mutation the major gene for radius incompletus (ri) were treated by standard light heat shock (37 degrees C 90 min) and heavy (transfer males from 37 2 hr to 4 1 back; this procedure was repeated three times). In F1 generation mated nontreated females same line, mass transpositions copia-like mobile genetic element Dm-412 found. The altered positions seem nonrandom; five "hot spots" transposition Probabilities estimated after in control...
It was recently shown that the brain-wide cerebrospinal fluid (CSF) and interstitial exchange system designated 'glymphatic pathway' plays a key role in removing waste products from brain, similarly to lymphatic other body organs . is therefore important study flow patterns of glymphatic transport through live brain order better understand its functionality normal pathological states. Unlike blood, CSF does not rapidly network dedicated vessels, but rather para-vascular channels parenchyma...
Extracting nuclei is one of the most actively studied topic in digital pathology researches. Most studies directly search (or seeds for nuclei) from finest resolution available. While richest information has been utilized by such approaches, it sometimes difficult to address heterogeneity different tissues. In this work, we propose a hierarchical approach which starts lower level and adaptively adjusts parameters while progressing into finer resolution. The algorithm tested on brain lung...
The phenomenon of transposition induction by heavy heat shock (HHS) was studied. Males a Drosophila isogenic line with mutation in the major gene radius incompletus ( ri ) were treated HHS (37 °C for 1 h followed 4 h, cycle repeated three times) and crossed to untreated females same line. males 5 d after shock, also 9 HHS. Many transpositions seen F1 larvae situ hybridization. rate induced at least 2 orders magnitude greater than that control sample, estimated be 0·11 events per transposable...
Digital histopathological images provide detailed spatial information of the tissue at micrometer resolution. Among available contents in pathology images, meso-scale information, such as gland morphology, texture, and distribution, are useful diagnostic features. In this work, focusing on colon-rectal cancer samples, we propose a multi-scale learning based segmentation scheme for glands digital slides. The algorithm learns non-gland textures from set training various scales through sparse...
The conflicting demands for simultaneous low-pass and high-pass processing, required in image denoising enhancement, still present an outstanding challenge, although a great deal of progress has been made by means adaptive diffusion-type algorithms. To further advance such processing methods algorithms, we introduce family second-order (in time) partial differential equations. These equations describe the motion thin elastic sheet damping environment. They are also derived variational...
Drug discovery typically consists of multiple steps, including identifying a target protein key to disease's etiology, validating that interacting with this could prevent symptoms or cure the disease, discovering small molecule biologic therapeutic interact it, and optimizing candidate through complex landscape required properties. related tasks often involve prediction generation while considering entities potentially interact, which poses challenge for typical AI models. For purpose we...
Image denoising and enhancement problems have many physical analogues that highlight new approaches to novel solutions. One such solution, based on viewing the image as elastic sheet, is presented. A processing scheme for grayscale images outlined further considered in context of color images. Preliminary analysis simulations noisy indicate multidimensional manifold representation combined space-color information incorporates advantages separate channel representations. Experimental reveals...
Image denoising and enhancement problems have many physical analogues that highlight new approaches to novel solutions. One such solution, based on viewing the image as elastic sheet, is presented. A processing scheme for grayscale images outlined further considered in context of color images. Preliminary analysis simulations noisy indicate multidimensional manifold representation combined space-color information incorporates advantages separate channel representations. Experimental reveals...
ABSTRACT It was recently shown that the brain-wide cerebrospinal fluid (CSF) and interstitial exchange system designated ‘glymphatic pathway’ plays a key role in removing waste products from brain, similarly to lymphatic other body organs 1,2 . is therefore important study flow patterns of glymphatic transport through live brain order better understand its functionality normal pathological states. Unlike blood, CSF does not rapidly network dedicated vessels, but rather peri-vascular channels...
N ikolay Vladimirovich Timofeeff-
Medical image classification involves thresholding of labels that represent malignancy risk levels. Usually, a task defines single threshold, and when developing computer-aided diagnosis tools, network is trained per such e.g. as screening out healthy (very low risk) patients to leave possibly sick ones for further analysis (low threshold), or trying find malignant cases among those marked non-risk by the radiologist ("second reading", high threshold). We propose way rephrase problem in...
The recently-proposed family of Telegraph-Diffusion (TeD) operators is analyzed in the context image enhancement. Stability such schemes terms energy convergence investigated and compared with that widely-used diffusion-based schemes, thereby resolving Perona-Malik paradox. results indicating stability are further generalized Forward-and-Backward (FAB) TeD enhancement operator. An approximated version operator offers an increased proposed examined. This scheme implemented both stable...
Deep neural networks have demonstrated impressive performance in various machine learning tasks. However, they are notoriously sensitive to changes data distribution. Often, even a slight change the distribution can lead drastic reduction. Artificially augmenting may help some extent, but most cases, fails achieve model invariance Some examples where this sub-class of domain adaptation be valuable imaging modalities such as thermal imaging, X-ray, ultrasound, and MRI, acquisition parameters...