Results 81 to 90 of about 931,369 (334)
Molecular Oncology, EarlyView.Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran +16 more
wiley +1 more source
Bayesian segmentation of hyperspectral images [PDF]
AIP Conference Proceedings, 2004 8 pages, 2 figures, presented at MaxEnt 2004, Inst.
Mohammadpour, Adel +2 more
openaire +5 more sources
Improved Depth Map Estimation from Stereo Images based on Hybrid Method [PDF]
, 2012 In this paper, a stereo matching algorithm based on image segments is presented. We propose the hybrid segmentation algorithm that is based on a combination of the Belief Propagation and Mean Shift algorithms with aim to refine the disparity and depth ...
Breznan, M. +4 more
core +1 more source
Targeted metabolomics reveals novel diagnostic biomarkers for colorectal cancer
Molecular Oncology, EarlyView.This study employed targeted metabolomic profiling to identify 302 distinct metabolites present in platelet‐rich plasma (PRP), revealing aberrant metabolic profiles amongst individuals diagnosed with colorectal cancer (CRC). Compared to carcinoembryonic antigen (CEA) and cancer antigen 19‐9 (CA199), our metabolite panel showed improved sensitivity ...
Zuojian Hu +7 more
wiley +1 more source
SN Applied Sciences, 2023 This paper mainly updates the image segmentation and multi-target recognition algorithm through the support vector machine algorithm in ML, and verifies the reliability of the new proposed algorithm through simulation experiments, and determines that the
Le Zhang
doaj +1 more source
Image Segmentation with Context [PDF]
, 2007 We present a technique for simultaneous segmentation and classification of image partitions using combinatorial optimization techniques. By combining existing image segmentation approaches with simple learning techniques we show how prior knowledge can be incorporated into the visual grouping process through the formulation of a quadratic binary ...
Eriksson, Anders +2 more
openaire +3 more sources
Visual-hint Boundary to Segment Algorithm for Image Segmentation [PDF]
, 2010 Image segmentation has been a very active research topic in image analysis area. Currently, most of the image segmentation algorithms are designed based on the idea that images are partitioned into a set of regions preserving homogeneous intra-regions ...
Dunham, Margaret H., Su, Yu
core
Molecular Oncology, EarlyView.Epithelial–mesenchymal transition (EMT) and tumor‐infiltrating lymphocytes (TILs) are associated with early breast cancer response to neoadjuvant chemotherapy (NAC). This study evaluated EMT and TIL shifts, with immunofluorescence and RNA sequencing, at diagnosis and in residual tumors as potential biomarkers associated with treatment response.
Françoise Derouane +16 more
wiley +1 more source
Clustering Approach Towards Image Segmentation: An Analytical Study [PDF]
International Journal of Research in Computer Applications and
Robotics, ISSN 2320-7345, Vol.2, Issue.7, Pg.: 115-124 July 2014, 2014 Image processing is an important research area in computer vision. Image segmentation plays the vital rule in image processing research. There exist so many methods for image segmentation. Clustering is an unsupervised study. Clustering can also be used for image segmentation.
arxiv
Molecular and functional profiling unravels targetable vulnerabilities in colorectal cancer
Molecular Oncology, EarlyView.We used whole exome and RNA‐sequencing to profile divergent genomic and transcriptomic landscapes of microsatellite stable (MSS) and microsatellite instable (MSI) colorectal cancer. Alterations were classified using a computational score for integrative cancer variant annotation and prioritization.
Efstathios‐Iason Vlachavas +15 more
wiley +1 more source