Human Organ

Human organ research currently focuses on improving the accuracy and efficiency of automated organ segmentation and localization from medical images like CT and MRI scans, primarily using deep learning models such as U-Net and its variants, along with transformer networks. These advancements aim to improve radiotherapy treatment planning by precisely identifying organs at risk and tumors, reducing manual workload and improving the accuracy of treatment. The resulting improvements in image analysis have significant implications for various medical applications, including surgical planning, disease diagnosis, and the development of more personalized treatments.

Papers

November 1, 2024

Deep learning-based auto-contouring of organs/structures-at-risk for pediatric upper abdominal radiotherapy
Mianyong Ding, Matteo Maspero, Annemieke S Littooij, Martine van Grotel, Raquel Davila Fajardo, Max M van Noesel, Marry M van den Heuvel-Eibrink, Geert O Janssens
Multi Organ Segmentation Patient Specific Inadequate Contour Encoding Human Organ Structural Damage Organ at Risk Pediatric Tumor Anatomical Sub Region

June 6, 2024

From Tissue Plane to Organ World: A Benchmark Dataset for Multimodal Biomedical Image Registration using Deep Co-Attention Networks
Yifeng Wang, Weipeng Li, Thomas Pearce, Haohan Wang
Benchmark Dataset Medical Image Registration Tissue Segmentation Human Organ Co Attention

May 17, 2024

Automatic segmentation of Organs at Risk in Head and Neck cancer patients from CT and MRI scans
Sébastien Quetin, Andrew Heschl, Mauricio Murillo, Rohit Murali, Shirin A. Enger, Farhad Maleki
Deep Learning Medical Image Segmentation Magnetic Resonance Imaging Automatic Segmentation Human Organ Neck Cancer MRI Scan Segmentation Pipeline MRI Volume

April 5, 2024

Deep-learning Segmentation of Small Volumes in CT images for Radiotherapy Treatment Planning
Jianxin Zhou, Kadishe Fejza, Massimiliano Salvatori, Daniele Della Latta, Gregory M. Hermann, Angela Di Fulvio
Deep Learning CT Image Accurate Segmentation Organ Segmentation Treatment Planning Small Scale Human Organ Small Object Segmentation

January 19, 2024

A novel method to compute the contact surface area between an organ and cancer tissue
Alessandra Bulanti, Alessandro Carfì, Paolo Traverso, Carlo Terrone, Fulvio Mastrogiovanni
New Method Mesh Reconstruction Tumor Cell Human Organ Contact Surface Tumor Shape

January 13, 2024

ORGANA: A Robotic Assistant for Automated Chemistry Experimentation and Characterization
Kourosh Darvish, Marta Skreta, Yuchi Zhao, Naruki Yoshikawa, Sagnik Som, Miroslav Bogdanovic, Yang Cao, Han Hao, Haoping Xu, Alán Aspuru-Guzik, Animesh Garg, Florian Shkurti
New Characterization Human Organ Laboratory Automation Electrochemical Model Robot Assistant

September 15, 2023

Large Intestine 3D Shape Refinement Using Point Diffusion Models for Digital Phantom Generation
Kaouther Mouheb, Mobina Ghojogh Nejad, Lavsen Dahal, Ehsan Samei, Kyle J. Lafata, W. Paul Segars, Joseph Y. Lo
Surface Reconstruction Polyp Phantom Surface Representation Human Organ Point Diffusion Colon Shape Estimation

September 11, 2023

Two-Stage Hybrid Supervision Framework for Fast, Low-resource, and Accurate Organ and Pan-cancer Segmentation in Abdomen CT
Wentao Liu, Tong Tian, Weijin Xu, Lemeng Wang, Haoyuan Li, Huihua Yang
Segmentation Performance Low Resource Tumor Segmentation Segmentation Accuracy Level Supervision Human Organ

May 4, 2023

Self-Supervised Learning for Organs At Risk and Tumor Segmentation with Uncertainty Quantification
Ilkin Isler, Debesh Jha, Curtis Lisle, Justin Rineer, Patrick Kelly, Bulent Aydogan, Mohamed Abazeed, Damla Turgut, Ulas Bagci
Self Supervised Learning Uncertainty Quantification Tumor Segmentation Self Supervised Pre Training High Quality Risk Description Human Organ

April 10, 2023

Localise to segment: crop to improve organ at risk segmentation accuracy
Abraham George Smith, Denis Kutnár, Ivan Richter Vogelius, Sune Darkner, Jens Petersen
Segmentation Network Segmentation Accuracy Well Defined Segment Crop Breeding Human Organ Medical Segmentation Decathlon

March 31, 2023

Comparing Adversarial and Supervised Learning for Organs at Risk Segmentation in CT images
Leonardo Crespi, Mattia Portanti, Daniele Loiacono
Generative Adversarial Network Supervised Learning CT Image Adversarial Text Human Organ GAN Generated Image Risk Segmentation Organ at Risk

March 19, 2023

Uncertainty Driven Bottleneck Attention U-net for Organ at Risk Segmentation
Abdullah Nazib, Riad Hassan, Zahidul Islam, Clinton Fookes
Medical Image Segmentation High Uncertainty Anticipation U Net Medical Image Segmentation Task Accurate Segmentation Human Organ Risk Segmentation Inaccurate Segmentation Decoder U Net

March 8, 2023

BOSS: Bones, Organs and Skin Shape Model
Karthik Shetty, Annette Birkhold, Srikrishna Jaganathan, Norbert Strobel, Bernhard Egger, Markus Kowarschik, Andreas Maier
Statistical Shape Human Organ Shape Model Bone Tissue

February 28, 2023

Interpretable and intervenable ultrasonography-based machine learning models for pediatric appendicitis
Ričards Marcinkevičs, Patricia Reis Wolfertstetter, Ugne Klimiene, Kieran Chin-Cheong, Alyssia Paschke, Julia Zerres, Markus Denzinger, David Niederberger, Sven Wellmann, Ece Ozkan, Christian Knorr, Julia E. Vogt
Ultrasound Image Concept Bottleneck Model Human Organ Pediatric Patient

February 21, 2023

Clinically Acceptable Segmentation of Organs at Risk in Cervical Cancer Radiation Treatment from Clinically Available Annotations
Monika Grewal, Dustin van Weersel, Henrike Westerveld, Peter A. N. Bosman, Tanja Alderliesten
Deep Learning Model Semi Supervised Learning Segmentation Mask High Quality Risk Description Automatic Segmentation Medical Annotation Human Organ

February 1, 2023

Continual Segment: Towards a Single, Unified and Accessible Continual Segmentation Model of 143 Whole-body Organs in CT Scans
Zhanghexuan Ji, Dazhou Guo, Puyang Wang, Ke Yan, Le Lu, Minfeng Xu, Jingren Zhou, Qifeng Wang, Jia Ge, Mingchen Gao, Xianghua Ye, Dakai Jin
Segmentation Model Computed Tomography Unified Alignment Multi Organ Segmentation Continual Semantic Segmentation Human Organ 2 Dimensional Segmentation Continual Segmentation Incremental Segmentation

October 21, 2022

August 21, 2022

Collaboration between parallel connected neural networks -- A possible criterion for distinguishing artificial neural networks from natural organs
Guang Ping He
Neural Network Human Organ Likely Criterion

March 1, 2022

A unified 3D framework for Organs at Risk Localization and Segmentation for Radiation Therapy Planning
Fernando Navarro, Guido Sasahara, Suprosanna Shit, Ivan Ezhov, Jan C. Peeken, Stephanie E. Combs, Bjoern H. Menze
Segmentation Based Approach Organ Segmentation 3D Representation Treatment Planning Medical Image Analysis Task Human Organ Organ at Risk Risk Localization

Human Organ

Papers

Deep learning-based auto-contouring of organs/structures-at-risk for pediatric upper abdominal radiotherapy

From Tissue Plane to Organ World: A Benchmark Dataset for Multimodal Biomedical Image Registration using Deep Co-Attention Networks

Automatic segmentation of Organs at Risk in Head and Neck cancer patients from CT and MRI scans

Deep-learning Segmentation of Small Volumes in CT images for Radiotherapy Treatment Planning

A novel method to compute the contact surface area between an organ and cancer tissue

ORGANA: A Robotic Assistant for Automated Chemistry Experimentation and Characterization

Large Intestine 3D Shape Refinement Using Point Diffusion Models for Digital Phantom Generation

Two-Stage Hybrid Supervision Framework for Fast, Low-resource, and Accurate Organ and Pan-cancer Segmentation in Abdomen CT

Self-Supervised Learning for Organs At Risk and Tumor Segmentation with Uncertainty Quantification

Localise to segment: crop to improve organ at risk segmentation accuracy

Comparing Adversarial and Supervised Learning for Organs at Risk Segmentation in CT images

Uncertainty Driven Bottleneck Attention U-net for Organ at Risk Segmentation

BOSS: Bones, Organs and Skin Shape Model

Interpretable and intervenable ultrasonography-based machine learning models for pediatric appendicitis

Clinically Acceptable Segmentation of Organs at Risk in Cervical Cancer Radiation Treatment from Clinically Available Annotations

Continual Segment: Towards a Single, Unified and Accessible Continual Segmentation Model of 143 Whole-body Organs in CT Scans

Learning shape distributions from large databases of healthy organs: applications to zero-shot and few-shot abnormal pancreas detection

A Multi-Arm Robotic Platform for Scientific Exploration

Collaboration between parallel connected neural networks -- A possible criterion for distinguishing artificial neural networks from natural organs

A unified 3D framework for Organs at Risk Localization and Segmentation for Radiation Therapy Planning