deep-learning-with-pytorch-for-medical-image-analysis-0

\ 0:00 COURSE OVERVIEW LECTURE - PLEASE DO NOT SKIP! 6:41 Installation and Environment Setup 24:30 Course Curriculum Course NumPy\ 25:49 Introduction to NumPy 28:04 NumPy Arrays 38:50 NumPy Arrays Part Two 47:00 NumPy Index Selection 59:17 NumPy Operations 1:06:03 NumPy Exercises 1:07:21 NumPy Exercise - Solutions Learning Concepts Overview\ 1:14:27 What is Machine Learning 1:18:07 Supervised Learning 1:26:28 Overfitting 1:34:27 Evaluating Performance - Classification Error Metrics 1:51:05 Evaluating Performance - Regression Error Metrics Basics\ 1:56:42 PyTorch Basics Introduction 2:00:03 Tensor Basics 2:08:13 Tensor Basics-Part Two 2:23:26 Tensor Operations 2:36:56 Tensor Operations-Part Two 2:43:23 PyTorch Basics - Exercise 2:45:56 PyTorch Basics - Exercise Solutions Neural Networks\ 2:51:18 Introduction to CNNs 2:52:22 Understanding the MNIST data set 2:55:47 ANN with MNIST - Part One - Data 3:15:09 ANN with MNIST - Part Two - Creating the Network 3:25:44 ANN with MNIST - Part Three - Training 3:41:13 ANN with MNIST - Part Four - Evaluation 3:50:28 Image Filters and Kernels 4:02:04 Convolutional Layers 4:16:05 Pooling Layers 4:22:52 MNIST Data Revisited 4:25:04 MNIST with CNN - Code Along - Part One 4:43:26 MNIST with CNN - Code Along - Part Two 5:01:45 MNIST with CNN - Code Along - Part Three 5:10:42 Why do we need GPUs 5:23:49 Using GPUs for PyTorch Imaging-A short Introduction\ 5:41:30 Introduction 5:46:47 Overview X-RAY 5:49:57 Overview CT 5:54:01 Overview MRI 5:57:20 Overview PET Formats in Medical Imaging\ 6:00:24 Introduction 6:02:20 DICOM 6:07:38 DICOM-in-Python 6:23:24 NIfTI 6:26:03 NIfTI-in-Python 6:35:22 Preprocessing 6:50:07 Preprocessing-in-Python-Part-1 7:03:22 Preprocessing-in-Python-Part-2 \ 7:15:32 Introduction 7:28:17 Preprocessing 7:43:38 Train-01-Data-Loading 7:57:17 Train-02-Model-Creation 8:09:41 Train-03-Trainer 8:13:57 Train-04-Evaluation 8:23:00 Interpretability \ 8:40:41 01-Introduction 8:46:12 02-Preprocessing 8:59:28 03-Dataset-Part-1 9:11:32 04-Dataset-Part-2 9:16:34 Train-01-Data-Loading 9:21:11 Train-02-Model-Creation 9:36:31 Train-03-Evaluation \ 9:43:24 01-Introduction 9:52:07 Preprocessing-01-Visualization 10:01:04 Preprocessing-02-Processing 10:09:05 Dataset-01-Dataset-Creation 10:17:52 Dataset-02-Dataset-Validation 10:21:53 UNet 10:36:11 Train-01-Data-Loading-and-Loss 10:42:06 Train-02-Model-Creation 10:51:37 Train-03-Evaluation Lung Tumor Segmentation\ 11:01:04 Introduction 11:05:59 Overview 11:07:09 Oversampling 11:13:00 Discussion Liver and Liver Tumor Segmentation\ 11:18:18 Introduction 11:29:37 Data-Visualization 11:34:44 Model 11:39:09 Train-01-TorchIO-Dataset 11:50:43 Train-02-Model-Creation 11:56:58 Train-03-Evaluation