Lesion Segmentation in Surgical and Diagnostic Applications: MICCAI 2022 Challenges, CuRIOUS 2022, KiPA 2022 and MELA 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18-22, 2022, Proceedings

This book includes peer-reviewed 10 papers from the Kidney Parsing Challenge 2022, Correction of Brain Shift with Intra-Operative Ultrasound-Segmentation Challenge (CuRIOUS-SEG 2022), and 2022 Mediastinal Lesion Analysis Challenge (MELA 2022).

Format: Paperback / softback
Length: 87 pages
Publication date: 14 March 2023
Publisher: Springer International Publishing AG

This book presents a collection of ten peer-reviewed papers that were submitted in response to three challenging tasks that were organized in conjunction with the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022. The papers included in this volume explore innovative solutions and methodologies for addressing critical issues in medical imaging and computer-assisted intervention.

The first challenge, the Kidney Parsing Challenge 2022: Multi-Structure Segmentation for Renal Cancer Treatment (KiPA 2022), aimed to develop accurate and efficient segmentation algorithms for kidney tumors. The challenge attracted a wide range of participants from around the world, and the submitted papers showcased a variety of techniques, including deep learning, convolutional neural networks, and graph-based methods.

The second challenge, the 2022 Correction of Brain Shift with Intra-Operative Ultrasound-Segmentation Challenge (CuRIOUS-SEG 2022), focused on developing accurate and robust methods for correcting brain shift during neurosurgical procedures. The challenge posed a significant technical challenge, as brain shift can have severe consequences for patient outcomes. The submitted papers addressed this challenge by leveraging advanced ultrasound imaging techniques, machine learning algorithms, and computer vision methods.

The third challenge, the 2022 Mediastinal Lesion Analysis Challenge (MELA 2022), aimed to develop automated algorithms for analyzing mediastinal lesions, such as lung tumors. The challenge required participants to develop methods for segmenting and characterizing these lesions, which can be challenging due to their complex anatomy and appearance. The submitted papers presented a range of innovative approaches, including deep learning, convolutional neural networks, and graph-based methods.

Overall, this book provides a valuable resource for researchers and practitioners in the field of medical imaging and computer-assisted intervention. The contributions made by the authors and participants showcase the latest advancements in this field and highlight the potential for innovative solutions to complex medical problems.

The first challenge, the Kidney Parsing Challenge 2022: Multi-Structure Segmentation for Renal Cancer Treatment (KiPA 2022), aimed to develop accurate and efficient segmentation algorithms for kidney tumors. The challenge attracted a wide range of participants from around the world, and the submitted papers showcased a variety of techniques, including deep learning, convolutional neural networks, and graph-based methods.

The second challenge, the 2022 Correction of Brain Shift with Intra-Operative Ultrasound-Segmentation Challenge (CuRIOUS-SEG 2022), focused on developing accurate and robust methods for correcting brain shift during neurosurgical procedures. The challenge posed a significant technical challenge, as brain shift can have severe consequences for patient outcomes. The submitted papers addressed this challenge by leveraging advanced ultrasound imaging techniques, machine learning algorithms, and computer vision methods.

The third challenge, the 2022 Mediastinal Lesion Analysis Challenge (MELA 2022), aimed to develop automated algorithms for analyzing mediastinal lesions, such as lung tumors. The challenge required participants to develop methods for segmenting and characterizing these lesions, which can be challenging due to their complex anatomy and appearance. The submitted papers presented a range of innovative approaches, including deep learning, convolutional neural networks, and graph-based methods.

Overall, this book provides a valuable resource for researchers and practitioners in the field of medical imaging and computer-assisted intervention. The contributions made by the authors and participants showcase the latest advancements in this field and highlight the potential for innovative solutions to complex medical problems.

Weight: 180g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031273230
Edition number: 1st ed. 2023