Wireless Capsule Endoscopy using Localization Techniques over IMU Sensor and Side-wall Cameras DOI
Sakshi Singh, Ranveer Singh

Опубликована: Дек. 16, 2022

Predicting the performance of wireless capsule endoscopy in human ileum has been a challenging topic for over decade. Considering its compact, coiled, and elongated shape, this makes sense. This paper suggests sensor-lens hybrid as solution to these issues through multisensory-aided WCE localization. The success connection is quantified here by RSSI. It recommended use Siamese Caps Net camera-based end result that accurate estimates are possible thanks method. One novel approach involves verifying Receiver's new location based on Round Trip Time, Communication Delay, Received Signal Strength Indication, Distance, Last Known Coordinates. Matlab R2019b then used calculate results. results demonstrate suggested method outperforms state-of-the-art methods terms Localization Accuracy, Standardized Root Mean Square Error, Average Translation Error.

Язык: Английский

Auto-WCEBleedGen Version V1 and V2: Challenge, Datasets and Evaluation DOI Creative Commons

Misa Hub,

Palak Handa,

Divyansh Nautiyal

и другие.

Authorea (Authorea), Год журнала: 2024, Номер unknown

Опубликована: Март 10, 2024

In this document, we provide an overview of the Auto-WCEBleedGen Version V1 and V2. The challenge was organized virtually by MISAHUB (Medical Imaging Signal Analysis) in collaboration with 8th International CVIP 2023 (Conference on Computer Vision Image Processing) from August 15-November 11, 2023. V2 is being

Язык: Английский

Процитировано

3

VCE-AnomalyNet: A New Dataset Fueling AI Precision in Anomaly Detection for Video Capsule Endoscopy ⋆ DOI Creative Commons

Advika Thakur,

Palak Handa,

Nidhi Goel

и другие.

Authorea (Authorea), Год журнала: 2024, Номер unknown

Опубликована: Апрель 23, 2024

Video capsule endoscopy (VCE) is a minimally invasive diagnostic technique that helps in the detection of various anomalies like polyps, ulcers, aphthae, etc, within intestinal lumen. Due to high no. frames VCE and low doctor-to-patient ratio across globe, inspection time about 2-4 hours. Research has shown Artificial Intelligence (AI) potential decrease reading improve upon false-positive rates. However, lack AI data big hindrance it. To address this issue, we present VCE-AnomalyNet Dataset, new dataset fueling precision anomaly for VCE. The comprises 108,832 accurately labeled with bounding box annotations YOLO (You Only Look Once) format. These have been compiled from multiple open-source datasets, aiming support research automatic available at Dataset (zenodo.org) .

Язык: Английский

Процитировано

2

Localization and Semantic Segmentation of Polyp in an Effort of Early Diagnosis of Colorectal Cancer from Wireless Capsule Endoscopy Images DOI

S Jothiraj,

Jayanthy Anavai Kandaswami

Опубликована: Ноя. 25, 2022

Cancer is characterized by the fast growth of aberrant cells that affect adjacent tissues. Colorectal cancer could be diagnosed in early stage identifying predecessor polyp are initially innocuous. Endoscopy aids identification real time monitoring. Polyps obscured mucosa surrounds it lumen colon, making visual differentiation from difficult for physicians thereby increasing miss rates. Recognizing colorectal polyps challenging as varies widely characteristics representing its features. With emergence deep learning techniques especially convolutional neural network an effort was made to detect and segment polyps. U-net architecture with capability learn features images proposed our paper semantic segmentation where colon localized. Polyp Kvasir dataset obtained using wireless capsule endoscopy provides advantage viewing entire gastrointestinal tract used this paper. The framework evaluated assessing performance optimized. predicted results produced accuracy, precision, sensitivity (recall), IoU f1 score 93.14%, 98.08%, 95.55%, 95.75% 98.01% respectively.

Язык: Английский

Процитировано

5

Open-Source Datasets for Colonoscopy Polyps and Its AI-Enabled Techniques DOI
Harshita Mangotra,

Palak Handa,

Nidhi Gooel

и другие.

Lecture notes in networks and systems, Год журнала: 2023, Номер unknown, С. 63 - 76

Опубликована: Янв. 1, 2023

Язык: Английский

Процитировано

1

CNN Architecture-Based Image Retrieval of Colonoscopy Polyp Frames DOI

Palak Handa,

Rishita Anand Sachdeva,

Nidhi Goel

и другие.

Lecture notes on data engineering and communications technologies, Год журнала: 2023, Номер unknown, С. 15 - 23

Опубликована: Янв. 1, 2023

Язык: Английский

Процитировано

1

Wireless Capsule Endoscopy using Localization Techniques over IMU Sensor and Side-wall Cameras DOI
Sakshi Singh, Ranveer Singh

Опубликована: Дек. 16, 2022

Predicting the performance of wireless capsule endoscopy in human ileum has been a challenging topic for over decade. Considering its compact, coiled, and elongated shape, this makes sense. This paper suggests sensor-lens hybrid as solution to these issues through multisensory-aided WCE localization. The success connection is quantified here by RSSI. It recommended use Siamese Caps Net camera-based end result that accurate estimates are possible thanks method. One novel approach involves verifying Receiver's new location based on Round Trip Time, Communication Delay, Received Signal Strength Indication, Distance, Last Known Coordinates. Matlab R2019b then used calculate results. results demonstrate suggested method outperforms state-of-the-art methods terms Localization Accuracy, Standardized Root Mean Square Error, Average Translation Error.

Язык: Английский

Процитировано

0