Канал: Kimia Lab

Foundation Models and Information Retrieval in Digital Pathology

Foundation Models and Information Retrieval in Digital Pathology

Image Search in Histopathology - The Past, Present, and the Path Forward

Image Search in Histopathology - The Past, Present, and the Path Forward

Learning or Searching in Digital Pathology

Learning or Searching in Digital Pathology

Kimia Lab - A Snapshot

Kimia Lab - A Snapshot

Matching Breast Biopsy Images to the Digital WHO Atlas

Matching Breast Biopsy Images to the Digital WHO Atlas

Pay Attention with Focus: A Novel Learning Scheme for Classification of Whole Slide Images

Pay Attention with Focus: A Novel Learning Scheme for Classification of Whole Slide Images

Digitizing Glass Slides to use AI for Computational Pathology

Digitizing Glass Slides to use AI for Computational Pathology

AI, Digital Pathology and Observer Variability: From Image Search to Building Diagnostic Consensus

AI, Digital Pathology and Observer Variability: From Image Search to Building Diagnostic Consensus

Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging

KimiaNet - Training a Histopathology Deep Network from Scratch

KimiaNet - Training a Histopathology Deep Network from Scratch

Recognizing Magnification Levels in Microscopic Snapshots - EMBC 2020

Recognizing Magnification Levels in Microscopic Snapshots - EMBC 2020

Supervision & Source Domain Impact on Representation Learning: A Histopathology Case Study -EMBC2020

Supervision & Source Domain Impact on Representation Learning: A Histopathology Case Study -EMBC2020

A Comparative Study of U-Net Topologies for Background Removal in Histopathology Images - IJCNN 2020

A Comparative Study of U-Net Topologies for Background Removal in Histopathology Images - IJCNN 2020

Fisher Discriminant Triplet and Contrastive Losses for Training Siamese Networks - IJCNN 2020

Fisher Discriminant Triplet and Contrastive Losses for Training Siamese Networks - IJCNN 2020

Representation Learning of Histopathology Images using Graph Neural Networks - CVPR 2020 CVMI

Representation Learning of Histopathology Images using Graph Neural Networks - CVPR 2020 CVMI

AI in Pathology - A Dell Technologies Video on Huron Digital Pathology and Kimia Lab

AI in Pathology - A Dell Technologies Video on Huron Digital Pathology and Kimia Lab

Image Search for Pan-Cancer Diagnostic Consensus - Dell Technologies Virtual HIMSS20 Webinar

Image Search for Pan-Cancer Diagnostic Consensus - Dell Technologies Virtual HIMSS20 Webinar

AI system more accurately identifies collapsed lungs using chest x-rays | CTV News

AI system more accurately identifies collapsed lungs using chest x-rays | CTV News

Can AI Agents be Ethical? (Ethics of Artificial intelligence in Medical Imaging)

Can AI Agents be Ethical? (Ethics of Artificial intelligence in Medical Imaging)

Introduction to Digital Pathology and AI Algorithms

Introduction to Digital Pathology and AI Algorithms

Machine Intelligence - Lecture 21 (Naive Bayes, Swarm Intelligence, Ant Colonies)

Machine Intelligence - Lecture 21 (Naive Bayes, Swarm Intelligence, Ant Colonies)

Machine Intelligence - Lecture 20 (Bayesian Learning, Bayes Theorem, Naive Bayes)

Machine Intelligence - Lecture 20 (Bayesian Learning, Bayes Theorem, Naive Bayes)

Machine Intelligence - Lecture 19 (Opposition-Based Learning, GAs, DE)

Machine Intelligence - Lecture 19 (Opposition-Based Learning, GAs, DE)

Machine Intelligence - Lecture 18 (Evolutionary Algorithms)

Machine Intelligence - Lecture 18 (Evolutionary Algorithms)

Machine Intelligence - Lecture 17 (Fuzzy Logic, Fuzzy Inference)

Machine Intelligence - Lecture 17 (Fuzzy Logic, Fuzzy Inference)

Machine Intelligence - Lecture 16 (Decision Trees)

Machine Intelligence - Lecture 16 (Decision Trees)

Machine Intelligence - Lecture 15 (Reinforcement Learning, Q-Learning)

Machine Intelligence - Lecture 15 (Reinforcement Learning, Q-Learning)

Machine Intelligence - Lecture 14 (Overfitting in Deep Learning, Reinforcement Learning)

Machine Intelligence - Lecture 14 (Overfitting in Deep Learning, Reinforcement Learning)

Image Search for Medical Imaging - Huron Digital Pathology

Image Search for Medical Imaging - Huron Digital Pathology

Machine Intelligence - Lecture 13 (Convolutional Neural Networks, CNNs)

Machine Intelligence - Lecture 13 (Convolutional Neural Networks, CNNs)

Machine Intelligence - Lecture 12 (Problems of Learning, RBMs, Autoencoders)

Machine Intelligence - Lecture 12 (Problems of Learning, RBMs, Autoencoders)

Machine Intelligence - Lecture 11 (Backpropagation, Topology, Overfitting, Autoencoders)

Machine Intelligence - Lecture 11 (Backpropagation, Topology, Overfitting, Autoencoders)

Machine Intelligence - Lecture 10 (Regression, Neurons, Perceptron, Learning)

Machine Intelligence - Lecture 10 (Regression, Neurons, Perceptron, Learning)

Machine Intelligence - Lecture 9 (Cluster Validity, Probability, Fuzzy Sets, FCM)

Machine Intelligence - Lecture 9 (Cluster Validity, Probability, Fuzzy Sets, FCM)

Machine Intelligence - Lecture 8 (SOM learning, Support Vector Machines)

Machine Intelligence - Lecture 8 (SOM learning, Support Vector Machines)

Machine Intelligence - Lecture 7 (Clustering, k-means, SOM)

Machine Intelligence - Lecture 7 (Clustering, k-means, SOM)

Machine Intelligence - Lecture 6 (Validation, Overfitting, Underfitting)

Machine Intelligence - Lecture 6 (Validation, Overfitting, Underfitting)

Machine Intelligence - Lecture 5 (Computer Vision, Features, Fisher Vector, VLAD)

Machine Intelligence - Lecture 5 (Computer Vision, Features, Fisher Vector, VLAD)

Machine Intelligence - Lecture 4 (LDA, t-SNE)

Machine Intelligence - Lecture 4 (LDA, t-SNE)

Machine Intelligence - Lecture 3 (PCA, AI and Data)

Machine Intelligence - Lecture 3 (PCA, AI and Data)

Machine Intelligence - Lecture 2 (Turing Test, Chinese Room, Generalization, PCA)

Machine Intelligence - Lecture 2 (Turing Test, Chinese Room, Generalization, PCA)

Machine Intelligence - Lecture 1 (methods, history, definitions, Turing Test)

Machine Intelligence - Lecture 1 (methods, history, definitions, Turing Test)

Artificial Intelligence - History, Opportunities & Challenges [Waterloo AI Institute Inaugural Talk]

Artificial Intelligence - History, Opportunities & Challenges [Waterloo AI Institute Inaugural Talk]

Ethics of Artificial Intelligence - Part 1 :: Machine Intelligence Course, Lecture 23

Ethics of Artificial Intelligence - Part 1 :: Machine Intelligence Course, Lecture 23

Ethics of Artificial Intelligence - Part 2 :: Machine Intelligence Course, Lecture 24

Ethics of Artificial Intelligence - Part 2 :: Machine Intelligence Course, Lecture 24

Medical Imaging: Pixels, Consensus and Learning

Medical Imaging: Pixels, Consensus and Learning

BIG Data, Medical Imaging and Machine Intelligence

BIG Data, Medical Imaging and Machine Intelligence

Automated Consensus Contouring - Reconcillio learns to generate consensus

Automated Consensus Contouring - Reconcillio learns to generate consensus

Segasist Cloud for Quality Assurance in Cancer Radiation Therapy

Segasist Cloud for Quality Assurance in Cancer Radiation Therapy

Auto-Contouring of Multiple Regions in Medical Images: Segasist's Fast Multi-Contouring

Auto-Contouring of Multiple Regions in Medical Images: Segasist's Fast Multi-Contouring

Prostate Segmentation: Segasist vs Manual Contouring

Prostate Segmentation: Segasist vs Manual Contouring

Segasist Technologies (Introduction) - Auto-Contouring Tools for Medical Images

Segasist Technologies (Introduction) - Auto-Contouring Tools for Medical Images

Segasist Intra-Patient Learning

Segasist Intra-Patient Learning

Segasist Editor

Segasist Editor

Contouring With Segasist (Part 2)

Contouring With Segasist (Part 2)

Simulation of Interactive Mode

Simulation of Interactive Mode

Contouring With Segasist (Part 1)

Contouring With Segasist (Part 1)

Training Segasist

Training Segasist

Setting Up Segasist

Setting Up Segasist