18 papers · ranked by Valyu relevance
Qingfu Wan, Weichao Qiu, Alan Yuille
State-of-the-art 3D human pose estimation approaches typically estimate pose from the entire RGB image in a single forward run. In this paper, we develop a post-processing step to refine 3D human pose estimation from body part patches. Using local patches as input has two advantages. First, the fine details around body…
Robert Harb, Thomas Pock, Heimo Müller
We present a novel diffusion-based approach to generate synthetic histopathological Whole Slide Images (WSIs) at an unprecedented gigapixel scale. Synthetic WSIs have many potential applications: They can augment training datasets to enhance the performance of many computational pathology applications. They allow the…
Roey Mechrez, Jacob Goldberger, Hayit Greenspan
This paper presents an automatic lesion segmentation method based on similarities between multichannel patches. A patch database is built using training images for which the label maps are known. For each patch in the testing image, k similar patches are retrieved from the database. The matching labels for these k…
Ankit Gupta, Alan Sabirsh, Carolina Wählby, Ida-Maria Sintorn
Large-scale microscopy-based experiments often result in images with rich but sparse information content. An experienced microscopist can visually identify regions of interest (ROIs), but this becomes a cumbersome task with large datasets. Here we present SimSearch, a framework for quick and easy user-guided training…
Soroush Oskouei, Marit Valla, André Pedersen, Erik Smistad + 9 more
Multi-Lens Distortion Authors: ['Soroush Oskouei' 'Marit Valla' 'André Pedersen' 'Erik Smistad' 'Vibeke Grotnes Dale' 'Maren Høibø' 'Sissel Gyrid Freim Wahl' 'Mats Dehli Haugum' 'Thomas Langø' 'Maria Ramnefjell' 'Lars A. Akslen' 'Gabriel Kiss' 'Hanne Sorger'] Considering the increased workload in pathology laboratories…
Danni Ai, Jian Yang, Jingfan Fan, Weijian Cong + 2 more
'Jie Tian'] Computed tomography (CT) has a revolutionized diagnostic radiology but involves large radiation doses that directly impact image quality. In this paper, we propose adaptive tensor-based principal component analysis (AT-PCA) algorithm for low-dose CT image denoising. Pixels in the image are presented by…
Tom Bisson, Michael Franz, Tim-Rasmus Kiehl, Peter Boor + 2 more
Purpose The paper presents a high-precision hierarchical registration method to accurately align image coordinates across Whole Slide Images of histopathological slides. The proposed technique was designed to achieve robust and pixel-precise stain- and scanner-independent colocalization. It addresses well-known…
Yun Zhang, Yu‐Kun Lai, Fang‐Lue Zhang
—This paper proposes an approach to contentpreserving image stitching with regular boundary constraints, which aims to stitch multiple images to generate a panoramic image with regular boundary. Existing methods treat image stitching and rectangling as two separate steps, which may result in suboptimal results as the…
Priyanka Mishra, Omead Amidi, Takeo Kanade
A surface is often modeled as a triangulated mesh of 3D points and textures associated with faces of the mesh. The 3D points could be either sampled from range data or derived from a set of images using a stereo or Structurefrom-Motion algorithm. When the points do not lie at critical points of maximum curvature or…
Mário A. T. Figueiredo
In global models/priors (for example, using wavelet frames), there is a well known analysis vs synthesis dichotomy in the way signal/image priors are formulated. In patch-based image models/priors, this dichotomy is also present in the choice of how each patch is modeled. This paper shows that there is another analysis…
Jun Zhang, Tong Zheng, Shengping Zhang, Meng Wang
—Computational color constancy refers to the estimation of the scene illumination and makes the perceived color relatively stable under varying illumination. In the past few years, deep Convolutional Neural Networks (CNNs) have delivered superior performance in illuminant estimation. Several representative methods…
Chongcong Jiang, Zhuo Zhao, Peixian Liang, Min Shi + 5 more
Whole slide image (WSI) classification is crucial in computational pathology, yet the gigapixel scale of WSIs makes it challenging to extract discriminative and compact WSI-level features for disease diagnosis. In this paper, we propose MambaWSI, a novel method that leverages the state space model (SSM) for WSI…
Adilson Berveglieri, Antonio M. G. Tommaselli
A technique for the reconstruction of cylindrical surfaces using optical images with an extension of least squares matching is presented. This technique is based on stereo-image acquisition of a cylindrical object, and it involves displacing the camera following the object length. The basic concept behind this…
William Speier, Jiayun Li, Wenyuan Li, Karthik Sarma + 1 more
Automated Gleason grading can be a valuable tool for physicians when assessing risk and planning treatment for prostate cancer patients. Semantic segmentation provides pixel-wise Gleason predictions across an entire slide, which can be more informative than classification of pre-selected homogeneous regions. Deep…
Lim Heo, Collin Arbour, Michael Feig
Protein structures provide valuable information for understanding biological processes. Protein structures can be determined by experimental methods such as X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, or cryogenic electron microscopy. As an alternative, in silico methods can be used to predict…
Yuelong Wu, Jeff W. Lichtman
Volume electron microscopy (vEM) is the most advanced and scalable technique for reconstructing synaptic-level wiring diagrams of the nervous system. Following image acquisition, the first critical step is reconstruction of a digitized volume, which assembles millions of electron microscope images into a coherent 3D…
Jürgen Köfinger, Gerhard Hummer
The proper balancing of information from experiment and theory is a long-standing problem in the analysis of noisy and incomplete data. Viewed as a Pareto optimization problem, improved agreement with the experimental data comes at the expense of growing inconsistencies with the theoretical reference model. Here, we…
Jürgen Köfinger, Gerhard Hummer
The proper balancing of information from experiment and theory is a long-standing problem in the analysis of noisy and incomplete data. Viewed as a Pareto optimization problem, improved agreement with the experimental data comes at the expense of growing inconsistencies with the theoretical reference model. Here, we…