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Save My Choices

AI-based Automatic
Blood Vessel Analysis
Software

Medical Research
Hub Solution

Automatic Contouring Server for radiation treatment

Accurate organ segmentation prior to radiotherapy leads to effective treatment.
Artificial intelligence performs organ segmentation in a short time.

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Conformity Certifications

MFDS

Republic of Korea
FDA

United States of America
PMDA

Japan
CE

Europe
TGA

Australia
HSA

Singapore
ANVISA

Brazil
HC

Canada

Automate organ segmentation

Automatically contours organs in short time.

49 organs are 100% automatically contoured by AI reducing the radiotherapy preparation time.

Head & Neck

22 Organs

· Brain

· Pituitary

· The brain stem

· Submandibular gland

· Eye

· Spinal cord

· The inner ear

· Thyroid

· Larynx

· Lymph node level 1a

· Lens

· Lymph node level 1b

· The mandible

· Lymph node level 2

· Optic chiasm

· Lymph node level 3

· Optic nerve

· Lymph node level 4a

· Oral cavity

· Lymph node level 4b

· The parotid gland

· Lymph node level 5

Breast

12 Organs

· Heart

· Internal mammary lymph nodes

· Breast

· Axillary lymph nodes Level 1

· Thyroid

· Axillary lymph nodes Level 2

· Esophagus

· Axillary lymph nodes Level 3

· Spinal cord

· Supraclavicular Lymph node (ESTRO)

· Lung

· Supraclavicular Lymph node (RTOG)

Abdomen

5 Organs

· Liver

· Kidney

· Stomach

· Spleen

· Duodenum

Pelvis

10 Organs

· Anorectum

· Cauda equina

· Bowel bag

· Femur

· Bladder

· Seminal vesicle

· Cervix

· Penile bulb

· Spinal cord

· Prostate

Automatically sends segmentation and contoured images.

Radiation treatment planning becomes more convenient.

The images are quickly and accurately contouring and automatically transmitted to the treatment plan system. A little final correction is required to complete contouring.
The quality of contouring is maintained consistent and free from working environment.

aview RT ACS Automatically sends segmentation and contoured images

Validations

Increase the accuracy of contouring and
reduce the time spent.

Increased accuracy

Manual contouring
0.881

DSC automatic contouring
0

Manual contouring
6.431
mm

HD automatic contouring
0
mm
Reduced the average contouring time

Manual
37
min

Automatic
0
min

Byun HK, Chang JS, Choi MS, Chun J, Jung J, Jeong C, Kim JS, Chang Y, Chung SY, Lee S, Kim YB. Evaluation of deep learning-based autosegmentation in breast cancer radiotherapy.
Radiat Oncol. 2021 Oct 14;16(1):203

Publications

Refer to the following research papers

These contents represent summaries of scientific
publications and are unrelated to any form of advertising.

This study evaluates the performance of aview RT-ACS in Coreline Soft, a deep learning-based automatic segmentation system that depicts at-risk organs (OARs) during breast radiotherapy.
The results showed that the accuracy of the automatic segmentation system is similar to that of manual segmentation by experts, with an average DSC value of 0.90.
The aview RT-ACS system has demonstrated good user satisfaction, highlighting the potential to improve the quality of breast radiotherapy and reducing variability among readers.

Byun HK, Chang JS, Choi MS, Chun J, Jung J, Jeong C, Kim JS, Chang Y, Chung SY, Lee S, Kim YB. Evaluation of deep learning-based autosegmentation in breast cancer radiotherapy. Radiat Oncol. 2021 Oct 14;16(1):203
This study evaluates the aview RT-ACS performance of coreline softs by comparing deep learning-based automatic segmentation contours of at-risk organs (OARs) in breast cancer patients receiving radiation therapy with manually depicted contours.
We demonstrated a high correlation with manual contours, achieving a Dice similarity coefficient of 0.80 or higher on all OARs and a Dice similarity coefficient of 0.70 or higher on all breast and local lymph node CTVs.
The study concluded that automatic segmentation using aview RT-ACS is feasible and beneficial for breast radiotherapy planning.

Chung SY, Chang JS, Choi MS, Chang Y, Choi BS, Chun J, Keum KC, Kim JS, Kim YB. Clinical feasibility of deep learning-based auto-segmentation of target volumes and organs-at-risk in breast cancer patients after breast-conserving surgery. Radiat Oncol. 2021 Feb 25;16(1):44.

More Publications

Automatic Contouring Server for radiation treatment

Accurate organ segmentation prior to radiotherapy leads to effective treatment. Artificial intelligence performs organ segmentation in a short time.

Automate organ segmentation

Automatically contours organs in short time.

49 organs are 100% automatically contoured by AI reducing the radiotherapy preparation time.

Automatically sends segmentation and contoured images.

Radiation treatment planning becomes more convenient.

The images are quickly and accurately contouring and automatically transmitted to the treatment plan system. A little final correction is required to complete contouring. The quality of contouring is maintained consistent and free from working environment.

Accurate organ segmentation prior to radiotherapy leads to effective treatment.
Artificial intelligence performs organ segmentation in a short time.

The images are quickly and accurately contouring and automatically transmitted to the treatment plan system. A little final correction is required to complete contouring.
The quality of contouring is maintained consistent and free from working environment.