AI SearchImproving GAN learning dynamics for thyroid nodule segmentation (Record no. 58846)
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|---|---|
| fixed length control field | 04147nas a2200433 a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260818134625.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 230202s2022 th m rtt 0| eng d |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | .b12398159 |
| 099 #9 - LOCAL FREE-TEXT CALL NUMBER (OCLC) | |
| Classification number | AIT Diss. no.ISE-22-01 |
| 100 0# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Alisa Kunapinun |
| 245 10 - TITLE STATEMENT | |
| Title | Improving GAN learning dynamics for thyroid nodule segmentation |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Pathum Thani, Thailand : |
| Name of publisher, distributor, etc. | Asian Institute of Technology, |
| Date of publication, distribution, etc. | 2022 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 83 leaves : |
| Other physical details | ill. +1 online resource |
| 490 1# - SERIES STATEMENT | |
| Series statement | Dissertation ; |
| Volume/sequential designation | no. ISE-22-01 |
| 500 ## - GENERAL NOTE | |
| General note | A dissertation submitted in partial fulfillment of the requirements for the degree of Doctoral of Engineering of Engineering in Mechatronics |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | Thesis (Ph. D.) - Asian Institute of Technology, 2022 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | The thyroid gland, which is responsible for secretion of critical hormones that regulate the body, is susceptible to a number of pathological conditions best diagnosed using ultrasound. A common diagnosis method involves identifying then characterizing the appearance of thyroid nodules: solid or fluid-filled lumps that could be benign or malignant. Physicians could be aided in this endeavor by an automated system to precisely identify nodules in a given ultrasound image. This thesis therefore presents a novel algorithm for segmenting thyroid nodules in ultrasound images named StableSeg GAN. The algorithm is based on the concept of image-to-image translation, which combines traditional supervised semantic segmentation with unsupervised learning using generative adversarial networks (GANs). GANs have been found to improve semantic segmentation models{u2019} performance in specific tasks. However, GAN learning dynamics are famously unstable, oftentimes leading to mode collapse. It is well known that controlling the discriminator in a GAN to not learn too quickly often improves generator learning, making the learning smoother and avoiding mode collapse. StableSeg GANs exploit the concept of closed-loop control of the gain on the loss output of the discriminator to stabilize training. We find that gain control leads to smoother generator training and avoids the mode collapse that typically occurs when the discriminator learns too quickly relative to the generator. We also find that the combination of the supervised and unsupervised learning styles encourages both low level accuracy and high-level consistency. As a test of the concept of controlled hybrid supervised and unsupervised semantic segmentation, StableSeg GANs use DeeplabV3+ as the generator, Resnet18 as the discriminator, and PID control to stabilize the GAN learning process. The new model is superior to the state-of-the-art DeeplabV3+ in terms of intersection over union (IoU), with a mean IoU of 81.26% over a challenging test set. The results of our thyroid nodule segmentation experiments show that StableSeg GANs have flexibility to segment nodules more accurately than supervised segmentation models or uncontrolled GANs. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Thyroid Nodule |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Deep learning |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Mongkol Ekpanyapong, |
| Relator term | Chairperson |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Dittapong Songsaeng, |
| Relator term | Co-Chairperson |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Siridech Boonsang, |
| Relator term | Examination committee |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Dailey, Mathew N., |
| Relator term | Examination Committee |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Manukid Parnichkun, |
| Relator term | Examination Committee |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Chadaporn Keatmanee, |
| Relator term | Examination committee |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | Royal Thai Government, |
| Relator term | Scholarship Donor |
| 810 2# - SERIES ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | Asian Institute of Technology. |
| Title of a work | Dissertation ; |
| Volume/sequential designation | no. ISE-22-01 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Materials specified | Full-Text |
| Uniform Resource Identifier | <a href="http://203.159.5.9/ait-thesis/detail.php?q=B18167">http://203.159.5.9/ait-thesis/detail.php?q=B18167</a> |
| 907 ## - LOCAL DATA ELEMENT G, LDG (RLIN) | |
| a | .b12398159 |
| b | mnait |
| c | m |
| 902 ## - LOCAL DATA ELEMENT B, LDB (RLIN) | |
| a | 250421 |
| 998 ## - LOCAL CONTROL INFORMATION (RLIN) | |
| Operator's initials, OID (RLIN) | 0 |
| Cataloger's initials, CIN (RLIN) | 230202 |
| First date, FD (RLIN) | m |
| -- | a |
| -- | m |
| -- | 0 |
| 945 ## - LOCAL PROCESSING INFORMATION (OCLC) | |
| l | mnarc |
| 945 ## - LOCAL PROCESSING INFORMATION (OCLC) | |
| l | mnait |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | 67-Electronic Resource |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | 20-AIT Publication |
| 909 ## - LOCAL ITEMS USED | |
| Barcode | Barcode : - |
| CREATED | CREATED : 2023-01-02 |
| RECORD Id | RECORD # : i13428846 |
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| 909 ## - LOCAL ITEMS USED | |
| Barcode | Barcode : 30050121076672 |
| CREATED | CREATED : 2023-09-02 |
| RECORD Id | RECORD # : i13431249 |
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| Withdrawn status | Lost status | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total checkouts | Full call number | Date last seen | Price effective from | Koha item type | Cost, normal purchase price | Barcode | Copy number |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 18/08/2026 | AIT Diss. no.ISE-22-01 | 18/08/2026 | 18/08/2026 | 67-Electronic Resource | |||||||
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | AIT Publications | 18/08/2026 | AIT Diss. no.ISE-22-01 | 18/08/2026 | 18/08/2026 | 20-AIT Publication | 50.00 | 30050121076672 | 1 |