Journals starting with bioi

BioIm17 * *Bio-Image Computing
* Automatic 3D Single Neuron Reconstruction with Exhaustive Tracing
* Bots for Software-Assisted Analysis of Image-Based Transcriptomics
* Computer-Automated Malaria Diagnosis and Quantitation Using Convolutional Neural Networks
* Count-ception: Counting by Fully Convolutional Redundant Counting
* Deep Convolutional Neural Networks for Detecting Cellular Changes Due to Malignancy
* Discovery of Rare Phenotypes in Cellular Images Using Weakly Supervised Deep Learning
* Dual Structured Convolutional Neural Network with Feature Augmentation for Quantitative Characterization of Tissue Histology
* Part-to-Whole Registration of Histology and MRI Using Shape Elements
* Particle Tracking Accuracy Measurement Based on Comparison of Linear Oriented Forests
* Siamese Networks for Chromosome Classification
* Solving Large Multicut Problems for Connectomics via Domain Decomposition
* Spatially-Variant Kernel for Optical Flow Under Low Signal-to-Noise Ratios Application to Microscopy
* Spheroid Segmentation Using Multiscale Deep Adversarial Networks
* Synthesising Wider Field Images from Narrow-Field Retinal Video Acquired Using a Low-Cost Direct Ophthalmoscope (Arclight) Attached to a Smartphone
* Towards a Spatio-Temporal Atlas of 3D Cellular Parameters During Leaf Morphogenesis
* Towards Virtual H E Staining of Hyperspectral Lung Histology Images Using Conditional Generative Adversarial Networks
* Virtual Blood Vessels in Complex Background Using Stereo X-Ray Images
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BioIm18 * *Bio-Image Computing
* 2D and 3D Vascular Structures Enhancement via Multiscale Fractional Anisotropy Tensor
* Automatic Classification of Low-Resolution Chromosomal Images
* Automatic Fusion of Segmentation and Tracking Labels
* Benchmark for Epithelial Cell Tracking, A
* Deep Convolutional Neural Networks Based Framework for Estimation of Stomata Density and Structure from Microscopic Images
* Densely Connected Stacked U-network for Filament Segmentation in Microscopy Images
* Detecting Synapse Location and Connectivity by Signed Proximity Estimation and Pruning with Deep Nets
* Fast and Scalable Pipeline for Stain Normalization of Whole-Slide Images in Histopathology, A
* Feature2Mass: Visual Feature Processing in Latent Space for Realistic Labeled Mass Generation
* Identification of C. elegans Strains Using a Fully Convolutional Neural Network on Behavioural Dynamics
* Improved Dictionary Learning with Enriched Information for Biomedical Images
* Instance Segmentation of Neural Cells
* Multi-level Activation for Segmentation of Hierarchically-Nested Classes
* Ordinal Regression with Neuron Stick-Breaking for Medical Diagnosis
* Pre-training on Grayscale ImageNet Improves Medical Image Classification
* Towards Automated Multiscale Imaging and Analysis in TEM: Glomerulus Detection by Fusion of CNN and LBP Maps
* Visual and Quantitative Comparison of Real and Simulated Biomedical Image Data
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BioIm23 * *Bio-Image Computing
* ACTIS: Improving data efficiency by leveraging semi-supervised Augmentation Consistency Training for Instance Segmentation
* Class-Guided Image-to-Image Diffusion: Cell Painting from Brightfield Images with Class Labels
* Complex-Valued Retrievals From Noisy Images Using Diffusion Models
* Deep Learning Framework using Sparse Diffusion MRI for Diagnosis of Frontotemporal Dementia
* DeepContrast: Deep Tissue Contrast Enhancement using Synthetic Data Degradations and OOD Model Predictions
* Direct Unsupervised Denoising
* Discrete Representation Learning for Modeling Imaging-based Spatial Transcriptomics Data
* Focus on Content not Noise: Improving Image Generation for Nuclei Segmentation by Suppressing Steganography in CycleGAN
* Generating Synthetic Computed Tomography (CT) Images to Improve the Performance of Machine Learning Model for Pediatric Abdominal Anomaly Detection
* Leveraging Classic Deconvolution and Feature Extraction in Zero-Shot Image Restoration
* NU-Net: a self-supervised smart filter for enhancing blobs in bioimages
* On the risk of manual annotations in 3D confocal microscopy image segmentation
* PCTrans: Position-Guided Transformer with Query Contrast for Biological Instance Segmentation
* Reinforcement learning for instance segmentation with high-level priors
* SortedAP: Rethinking evaluation metrics for instance segmentation
* Spatio-Temporal Analysis of Patient-Derived Organoid Videos Using Deep Learning for the Prediction of Drug Efficacy
* Towards Hierarchical Regional Transformer-based Multiple Instance Learning
* Transformer-based Detection of Microorganisms on High-Resolution Petri Dish Images
* TYC Dataset for Understanding Instance-Level Semantics and Motions of Cells in Microstructures, The
* Virtual perturbations to assess explainability of deep-learning based cell fate predictors
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BioImage15 * *BioImage Computing Workshop
* Deep neural networks for anatomical brain segmentation
* Fast registration of segmented images by normal sampling
* From photography to microbiology: Eigenbiome models for skin appearance

BioImage16 * *BioImage Computing Workshop
* 3-D Density Kernel Estimation for Counting in Microscopy Image Volumes Using 3-D Image Filters and Random Decision Trees
* Automatic Detection and Segmentation of Exosomes in Transmission Electron Microscopy
* Cell Counting by Regression Using Convolutional Neural Network
* Deep Convolutional Neural Networks for Human Embryonic Cell Counting
* Dendritic Spine Shape Analysis: A Clustering Perspective
* Feature Augmented Deep Neural Networks for Segmentation of Cells
* Histopathology Image Categorization with Discriminative Dimension Reduction of Fisher Vectors
* Measuring Process Dynamics and Nuclear Migration for Clones of Neural Progenitor Cells
* Poisson Point Processes for Solving Stochastic Inverse Problems in Fluorescence Microscopy
* Single-Image Insect Pose Estimation by Graph Based Geometric Models and Random Forests
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BioImage22 * *BioImage Computing Workshop
* Characterization of AI Model Configurations for Model Reuse
* Comparison of Semi-supervised Learning Methods for High Content Screening Quality Control
* Discriminative Attribution from Paired Images
* Empirical Evaluation of Deep Learning Approaches for Landmark Detection in Fish Bioimages
* Learning with Minimal Effort: Leveraging in Silico Labeling for Cell and Nucleus Segmentation
* N2V2 - Fixing Noise2void Checkerboard Artifacts with Modified Sampling Strategies and a Tweaked Network Architecture
* Pointfish: Learning Point Cloud Representations for RNA Localization Patterns
* Towards Better Guided Attention and Human Knowledge Insertion in Deep Convolutional Neural Networks
* Towards Structured Noise Models for Unsupervised Denoising
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BioImaging(2) * 3-D Texture Characterized by Accessibility Measurements, Based on the Grey Weighted Distance Transform

BioInfo05 * Classification of Proteomic Data with Logistic Kernel Partial Least Squares Algorithm
* Discovery of Prokaryotic Relationships through Latent Structure of Correlated Nucleotide Sequences
* Extended-Regular Sequence for Automated Analysis of Microarray Images
* Gene Selection via a Spectral Approach
* Identifying Genes with The Concept of Customization
* Overview of DNA Microarray Image Requirements for Automated Processing, An
* Pattern Recognition Method to Detect Vulnerable Spots in an RNA Sequence for Bacterial Resistance to the Antibiotic Spectinomycin
* Protein Interaction Inference as a MAX-SAT Problem
* Reliable Tracking of Large Scale Dense Antiparallel Particle Motion for Fluorescence Live Cell Imaging
* Tracking Cell Signals in Fluorescent Images
* Tracking Single Quantum Dots in Live Cells with Minimal Paths
* Wavelet Transformation for Temporal Gene Expression Analysis, The
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Index for "b"


Last update:16-Mar-24 21:12:13
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