Results 51 to 60 of about 155,901 (241)

Possibility Study of Scale Invariant Feature Transform (SIFT) Algorithm Application to Spine Magnetic Resonance Imaging. [PDF]

PLoS ONE, 2016
The purpose of this study is an application of scale invariant feature transform (SIFT) algorithm to stitch the cervical-thoracic-lumbar (C-T-L) spine magnetic resonance (MR) images to provide a view of the entire spine in a single image.
Dong-Hoon Lee, Do-Wan Lee, Bong-Soo Han
doaj   +1 more source

Salient Local 3D Features for 3D Shape Retrieval

, 2011
In this paper we describe a new formulation for the 3D salient local features based on the voxel grid inspired by the Scale Invariant Feature Transform (SIFT).
Godil, Afzal, Wagan, Asim Imdad
core   +1 more source

The atypical KRASQ22K mutation directs TGF‐β response towards partial epithelial‐to‐mesenchymal transition in patient‐derived colorectal cancer tumoroids

Molecular Oncology, EarlyView.
TGF‐β has a complex role in cancer, exhibiting both tumor‐suppressive and tumor‐promoting properties. Using a series of differentiated tumoroids, derived from different stages and mutational background of colorectal cancer patients, we replicate this duality of TGF‐β in vitro. Notably, the atypical but highly aggressive KRASQ22K mutation rendered early‐
Theresia Mair, Philip König, Milena Mijović, Jessica Kalla, Anil Baskan, Loan Tran, Kristina Draganić, Pedro Morata Saldaña, Carlos Uziel Pérez Malla, Janette Pfneissl, Andreas Tiefenbacher, Julijan Kabiljo, Velina S. Atanasova, Lisa Wozelka‐Oltjan, Leonhard Müllauer, Michael Bergmann, Raheleh Sheibani‐Tezerji, Gerda Egger   +17 more
wiley   +1 more source

A Full-Featured FPGA-Based Pipelined Architecture for SIFT Extraction

IEEE Access, 2021
Image feature detection is a key task in computer vision. Scale Invariant Feature Transform (SIFT) is a prevalent and well known algorithm for robust feature detection.
Philipp Kreowsky, Benno Stabernack
doaj   +1 more source

Parallelizing Scale Invariant Feature Transform on a Distributed Memory Cluster [PDF]

, 2011
Scale Invariant Feature Transform (SIFT) is a computer vision algorithm that is widely-used to extract features from images. We explored accelerating an existing implementation of this algorithm with message passing in order to analyze large data sets ...
Bobovych, Stanislav
core   +2 more sources

Time, the final frontier

Molecular Oncology, EarlyView.
This article advocates integrating temporal dynamics into cancer research. Rather than relying on static snapshots, researchers should increasingly consider adopting dynamic methods—such as live imaging, temporal omics, and liquid biopsies—to track how tumors evolve over time.
Gautier Follain, Michal Dibus, Omkar Joshi, Guillaume Jacquemet   +3 more
wiley   +1 more source

A Zero-Watermarking Algorithm Based on Scale-Invariant Feature Reconstruction Transform

Applied Sciences
In order to effectively protect and verify the copyright information of multimedia digital works, this paper proposes a zero-watermarking algorithm based on carrier image feature point descriptors.
Fan Li, Zhong-Xun Wang
doaj   +1 more source

Learning Robust Feature Descriptor for Image Registration With Genetic Programming

IEEE Access, 2020
The robustness and accuracy of feature descriptor are two essential factors in the process of image registration. Existing feature descriptors can extract important image features, but it may be difficult to find enough correct correspondences for ...
Yue Wu, Qingxiu Su, Wenping Ma, Shaodi Liu, Qiguang Miao   +4 more
doaj   +1 more source

Linear Spatial Pyramid Matching Using Non-convex and non-negative Sparse Coding for Image Classification

, 2015
Recently sparse coding have been highly successful in image classification mainly due to its capability of incorporating the sparsity of image representation.
Bao, Chengqiang, He, Liangtian, Wang, Yilun   +2 more
core   +1 more source

Aberrant expression of nuclear prothymosin α contributes to epithelial‐mesenchymal transition in lung cancer

Molecular Oncology, EarlyView.
Nuclear prothymosin α inhibits epithelial‐mesenchymal transition (EMT) in lung cancer by increasing Smad7 acetylation and competing with Smad2 for binding to SNAI1, TWIST1, and ZEB1 promoters. In early‐stage cancer, ProT suppresses TGF‐β‐induced EMT, while its loss in the nucleus in late‐stage cancer leads to enhanced EMT and poor prognosis.
Liyun Chen, Chung‐Teng Wang, Jia‐Ming Chang, Ai‐Li Shiau, Gia‐Shing Shieh, Yau‐Lin Tseng, Yi‐Ting Yen, Tang‐Hsiu Huang, Li‐Hsin Cheng, Yu‐Chih Wu, Chao‐Liang Wu, Bing‐Hua Su, Pensee Wu   +12 more
wiley   +1 more source