Browse > Methodology > Computed Tomography (CT)

Computed Tomography (CT)

38 papers with code · Methodology

The term “computed tomography”, or CT, refers to a computerized x-ray imaging procedure in which a narrow beam of x-rays is aimed at a patient and quickly rotated around the body, producing signals that are processed by the machine's computer to generate cross-sectional images—or “slices”—of the body.

( Image credit: Liver Lesion Detection from Weakly-labeled Multi-phase CT Volumes with a Grouped Single Shot MultiBox Detector )

Leaderboards

You can find evaluation results in the subtasks. You can also submitting evaluation metrics for this task.

Greatest papers with code

MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation

12 Aug 2019facebookresearch/maskrcnn-benchmark

When reading medical images such as a computed tomography (CT) scan, radiologists generally search across the image to find lesions, characterize and measure them, and then describe them in the radiological report.

COMPUTED TOMOGRAPHY (CT)

Improving RetinaNet for CT Lesion Detection with Dense Masks from Weak RECIST Labels

5 Jun 2019fizyr/keras-retinanet

We propose a highly accurate and efficient one-stage lesion detector, by re-designing a RetinaNet to meet the particular challenges in medical imaging.

COMPUTED TOMOGRAPHY (CT) SKIN LESION IDENTIFICATION

UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation

11 Dec 2019MrGiovanni/UNetPlusPlus

The state-of-the-art models for medical image segmentation are variants of U-Net and fully convolutional networks (FCN).

COMPUTED TOMOGRAPHY (CT) INSTANCE SEGMENTATION MEDICAL IMAGE SEGMENTATION SEMANTIC SEGMENTATION

ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction

3 Aug 2019JunMa11/MICCAI2019-OpenSourcePapers

Current deep neural network based approaches to computed tomography (CT) metal artifact reduction (MAR) are supervised methods that rely on synthesized metal artifacts for training.

COMPUTED TOMOGRAPHY (CT) IMAGE-TO-IMAGE TRANSLATION MEDICAL IMAGE GENERATION METAL ARTIFACT REDUCTION

The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomes

31 Mar 2019neheller/kits19

The morphometry of a kidney tumor revealed by contrast-enhanced Computed Tomography (CT) imaging is an important factor in clinical decision making surrounding the lesion's diagnosis and treatment.

COMPUTED TOMOGRAPHY (CT) DECISION MAKING SEMANTIC SEGMENTATION

Generative Adversarial Networks for Image-to-Image Translation on Multi-Contrast MR Images - A Comparison of CycleGAN and UNIT

20 Jun 2018simontomaskarlsson/GAN-MRI

Here, we evaluate two unsupervised GAN models (CycleGAN and UNIT) for image-to-image translation of T1- and T2-weighted MR images, by comparing generated synthetic MR images to ground truth images.

COMPUTED TOMOGRAPHY (CT) IMAGE-TO-IMAGE TRANSLATION MEDICAL IMAGE GENERATION

DeepLung: Deep 3D Dual Path Nets for Automated Pulmonary Nodule Detection and Classification

25 Jan 2018uci-cbcl/DeepLung

DeepLung consists of two components, nodule detection (identifying the locations of candidate nodules) and classification (classifying candidate nodules into benign or malignant).

COMPUTED TOMOGRAPHY (CT) LUNG NODULE CLASSIFICATION

Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction

5 Jun 2019liaohaofu/adn

Extensive experiments show that our method significantly outperforms the existing unsupervised models for image-to-image translation problems, and achieves comparable performance to existing supervised models on a synthesized dataset.

COMPUTED TOMOGRAPHY (CT) IMAGE-TO-IMAGE TRANSLATION METAL ARTIFACT REDUCTION

Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy

12 Sep 2018deepmind/tcia-ct-scan-dataset

Adopting a deep learning approach, we demonstrate a 3D U-Net architecture that achieves performance similar to experts in delineating a wide range of head and neck OARs.

COMPUTED TOMOGRAPHY (CT)