22 results on '"Shamsil A"'
Search Results
2. Texture-based Intraoperative Image Guidance for Tumor Localization in Minimally Invasive Surgery.
- Author
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Arefin Shamsil, Michael D. Naish, and Rajni V. Patel
- Published
- 2021
- Full Text
- View/download PDF
3. Comprehensive metrics for evaluating surgical microscope use during tympanostomy tube placement
- Author
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Wickens, Brandon, Shamsil, Arefin, Husein, Murad, Nguyen, Lily H. P., Doyle, Philip C., Parnes, Lorne S., Agrawal, Sumit K., and Ladak, Hanif M.
- Published
- 2021
- Full Text
- View/download PDF
4. Comprehensive metrics for evaluating surgical microscope use during tympanostomy tube placement.
- Author
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Brandon Wickens, Arefin Shamsil, Murad Husein, Lily H. P. Nguyen, Philip C. Doyle, Lorne S. Parnes, Sumit K. Agrawal, and Hanif M. Ladak
- Published
- 2021
- Full Text
- View/download PDF
5. ‘Khep’: Exploring Factors that Influence The Preference of Contractual Rides to Ride-Sharing Apps in Bangladesh
- Author
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Alok, Aditto Baidya, primary, Sakib, Hasibul, additional, Ullah, Shamsil Arafin, additional, Huq, Fardin, additional, Ghosh, Riya, additional, Mondal, Joyanta Jyoti, additional, Sakif, Md. Sadiqul Islam, additional, and Noor, Jannatun, additional
- Published
- 2023
- Full Text
- View/download PDF
6. A multi-sensory mechatronic device for localizing tumors in minimally invasive interventions.
- Author
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Abelardo Escoto, Srikanth Bhattad, Arefin Shamsil, Andre Sanches, Ana Luisa Trejos, Michael D. Naish, Richard Malthaner, and Rajni V. Patel
- Published
- 2015
- Full Text
- View/download PDF
7. Integrating e-Learning with Radio Frequency Identification (RFID) for Learning Disabilities: A Preliminary Study
- Author
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Yahya, Wan Fatin Fatihah, Noor, Noor Maizura Mohamad, Hamzah, Mohd Pouzi, Hassan, Mohamad Nor, Mamat, Nur Fadila Akma, Rifin, Mohd Arizal Shamsil Mat, Sulaiman, Hamzah Asyrani, editor, Othman, Mohd Azlishah, editor, Othman, Mohd Fairuz Iskandar, editor, Rahim, Yahaya Abd, editor, and Pee, Naim Che, editor
- Published
- 2015
- Full Text
- View/download PDF
8. Comprehensive metrics for evaluating surgical microscope use during tympanostomy tube placement
- Author
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Murad Husein, Brandon Wickens, Arefin Shamsil, Hanif M. Ladak, Philip C. Doyle, Lorne S. Parnes, Lily H. P. Nguyen, and Sumit K. Agrawal
- Subjects
medicine.medical_specialty ,Computer science ,medicine.medical_treatment ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Biomedical Engineering ,Health Informatics ,Health informatics ,Myringotomy ,03 medical and health sciences ,0302 clinical medicine ,medicine ,Radiology, Nuclear Medicine and imaging ,Medical physics ,Tympanostomy tube ,Surgical microscope ,business.industry ,Construct validity ,Objective method ,General Medicine ,Computer Graphics and Computer-Aided Design ,Computer Science Applications ,Otorhinolaryngology ,030211 gastroenterology & hepatology ,Surgery ,Computer Vision and Pattern Recognition ,Completion time ,business ,030217 neurology & neurosurgery - Abstract
Learning to use a surgical microscope is a fundamental step in otolaryngology training; however, there is currently no objective method to teach or assess this skill. Tympanostomy tube placement is a common otologic procedure that requires skilled use of a surgical microscope. This study was designed to (1) implement metrics capable of evaluating microscope use and (2) establish construct validity. This was a prospective cohort study. Eight otolaryngology trainees and three otolaryngology experts were asked to use a microscope to insert a tympanostomy tube into a cadaveric myringotomy in a standardized setting. Microscope movements were tracked in a three-dimensional space, and tracking metrics were applied to the data. The procedure was video-recorded and then analyzed by blinded experts using operational metrics. Results from both groups were compared, and discriminatory metrics were determined. The following tracking metrics were identified as discriminatory between the trainee and expert groups: total completion time, operation time, still time, and jitter (movement perturbation). Many operational metrics were found to be discriminatory between the two groups, including several positioning metrics, optical metrics, and procedural metrics. Performance metrics were implemented, and construct validity was established for a subset of the proposed metrics by discriminating between expert and novice participants. These discriminatory metrics could form the basis of an automated system for providing feedback to residents during training while using a myringotomy surgical simulator. Additionally, these metrics may be useful in guiding a standardized teaching and evaluation methodology for training in the use of surgical microscopes.
- Published
- 2021
9. A computational model for estimating tumor margins in complementary tactile and 3D ultrasound images.
- Author
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Arefin Shamsil, Abelardo Escoto, Michael D. Naish, and Rajni V. Patel
- Published
- 2016
- Full Text
- View/download PDF
10. Texture-based Intraoperative Image Guidance for Tumor Localization in Minimally Invasive Surgery
- Author
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Shamsil, Arefin, primary, Naish, Michael D., additional, and Patel, Rajni V., additional
- Published
- 2021
- Full Text
- View/download PDF
11. Integrating e-Learning with Radio Frequency Identification (RFID) for Learning Disabilities: A Preliminary Study
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Yahya, Wan Fatin Fatihah, primary, Noor, Noor Maizura Mohamad, additional, Hamzah, Mohd Pouzi, additional, Hassan, Mohamad Nor, additional, Mamat, Nur Fadila Akma, additional, and Rifin, Mohd Arizal Shamsil Mat, additional
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- 2014
- Full Text
- View/download PDF
12. Teaching and Learning Module on Learning Disabilities (LD) Using RFID Technology
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Rosmayati Mohemad, Mohd Arizal Shamsil Mat Rifin, Mohamad Nor Hassan, Noor Maizura Mohamad Noor, Nur Fadila Akma Mamat, Wan Fatin Fatihah Yahya, and Mohd Pouzi Hamzah
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Multimedia ,Learning disability ,medicine ,medicine.symptom ,Psychology ,computer.software_genre ,computer - Published
- 2017
13. A computational model for estimating tumor margins in complementary tactile and 3D ultrasound images
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Rajni V. Patel, Abelardo Escoto, Arefin Shamsil, and Michael D. Naish
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0209 industrial biotechnology ,intraoperative imaging ,tumor margins ,Computer science ,Tactile imaging ,tumor localization ,02 engineering and technology ,Palpation ,multisensory image visualization ,030218 nuclear medicine & medical imaging ,03 medical and health sciences ,020901 industrial engineering & automation ,0302 clinical medicine ,medicine ,Fluoroscopy ,3D ultrasound ,Computer vision ,tactile image fusion ,medicine.diagnostic_test ,business.industry ,Ultrasound ,Image segmentation ,histogram based classification ,Invasive surgery ,intraoperative ultrasound imaging ,Ultrasonic sensor ,Artificial intelligence ,business ,Ex vivo - Abstract
Conventional surgical methods are effective for treating lung tumors; however, they impose high trauma and pain to patients. Minimally invasive surgery is a safer alternative as smaller incisions are required to reach the lung; however, it is challenging due to inadequate intraoperative tumor localization. To address this issue, a mechatronic palpation device was developed that incorporates tactile and ultrasound sensors capable of acquiring surface and cross-sectional images of palpated tissue. Initial work focused on tactile image segmentation and fusion of position-tracked tactile images, resulting in a reconstruction of the palpated surface to compute the spatial locations of underlying tumors. This paper presents a computational model capable of analyzing orthogonally-paired tactile and ultrasound images to compute the surface circumference and depth margins of a tumor. The framework also integrates an error compensation technique and an algebraic model to align all of the image pairs and to estimate the tumor depths within the tracked thickness of a palpated tissue. For validation, an ex vivo experimental study was conducted involving the complete palpation of 11 porcine liver tissues injected with iodine-agar tumors of varying sizes and shapes. The resulting tactile and ultrasound images were then processed using the proposed model to compute the tumor margins and compare them to fluoroscopy based physical measurements. The results show a good negative correlation ( r = −0.783, p = 0.004) between the tumor surface margins and a good positive correlation ( r = 0.743, p = 0.009) between the tumor depth margins.
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- 2016
14. A multi-sensory mechatronic device for localizing tumors in minimally invasive interventions
- Author
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Srikanth Bhattad, Richard A. Malthaner, Ana Luisa Trejos, Abelardo Escoto, Andre Sanches, Michael D. Naish, Arefin Shamsil, and Rajni V. Patel
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medicine.diagnostic_test ,business.industry ,medicine.medical_treatment ,Ultrasound ,Soft tissue ,Tumor Pathology ,Palpation ,Imaging phantom ,Multi sensory ,medicine ,Thoracotomy ,Lung resection ,business ,Biomedical engineering - Abstract
Tumor localization in traditional lung resection surgery requires manual palpation of the deflated lung through a thoracotomy. It is a painful procedure that is not suitable for many patients. Therefore, a multisensory mechatronic device was designed to localize tumors using a minimally invasive approach. The device is sensorized with tactile, ultrasound and position sensors in order to obtain multimodal data of soft tissue in real time. This paper presents the validation of the efficiency and efficacy of this device via an ex vivo experimental study. Tumor pathology was simulated by embedding iodine-agar phantom tumors of varying shapes and sizes into porcine liver tissue. The device was then used to palpate the tissue to localize and visualize the simulated tumors. Markers were then placed on the location of the tumors and fluoroscopic imaging was performed on the tissue in order to determine the localization accuracy of the device. Our results show that the device localized 87.5% of the tumors with an average deviation from the tumor center of 3.42 mm.
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- 2015
15. Integrating e-Learning with Radio Frequency Identification (RFID) for Learning Disabilities: A Preliminary Study
- Author
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Noor Maizura Mohamad Noor, Mohamad Nor Hassan, Mohd Pouzi Hamzah, Mohd Arizal Shamsil Mat Rifin, Nur Fadila Akma Mamat, and Wan Fatin Fatihah Yahya
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Learning styles ,Engineering ,business.industry ,Process (engineering) ,Human–computer interaction ,E-learning (theory) ,Learning disability ,medicine ,Radio-frequency identification ,Kinesthetic learning ,medicine.symptom ,business ,Educational systems - Abstract
Integrating learning styles in adaptive educational systems are a growing trend in technology enhanced learning. Children have different learning styles, abilities, preferences that focus on different types of information and process new information in different ways. Providing adaptively based on learning styles can promote interest for learners and make learning easier for them. The purpose of our research is to adopt an e-Learning approach Radio Frequency Identification (RFID) technology in order to model the Visual, Auditory and Kinesthetic (VAK) learning style focused on Learning Disabilities (LD) children. Today’s technology offers great chances to assist students with disabilities to live freely and learn more easily. Developing the learning environments assisted by technology is a new way in making their learning processes successful.
- Published
- 2014
16. A computational model for estimating tumor margins in complementary tactile and 3D ultrasound images
- Author
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Shamsil, Arefin, additional, Escoto, Abelardo, additional, Naish, Michael D., additional, and Patel, Rajni V., additional
- Published
- 2016
- Full Text
- View/download PDF
17. Metrics for Evaluating Surgical Microscope Usage During Myringotomy
- Author
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Shamsil, Arefin M
- Subjects
training ,Biomedical ,Surgical microscope ,myringotomy ,Biological Engineering ,education ,Signal Processing ,otorhinolaryngologic diseases ,Systems and Integrative Engineering ,performance metrics ,Bioimaging and Biomedical Optics ,Biomedical Devices and Instrumentation - Abstract
Although teaching and learning surgical microscope manoeuvring is a fundamental step in middle ear surgical training, currently there is no objective method to teach or assess this skill. This thesis presents an experimental study designed to implement and test sets of metrics capable of numerically evaluating microscope manoeuvrability and qualitatively assessing surgical expertise of a subject during a middle ear surgery called myringotomy. The experiment involved performing a myringotomy on a fixed cadaveric ear. As participants, experienced ear-nose-throat (ENT) surgeons and ENT surgical residents were invited. While performing the procedure, their microscope manoeuvring motions were captured as translational and angular coordinates using an optical tracker. These data were analyzed in terms of motion path length, velocity, acceleration, jitter, manoeuvring volume, smoothness, rotation and time. Participants’ hand motion, body posture and microscopic view were also video recorded to qualitatively assess their surgical expertise. Several metrics were statistically identified as discriminatory. These metrics will be incorporated into a myringotomy surgical simulator to train ENT residents.
- Published
- 2012
18. A multi-sensory mechatronic device for localizing tumors in minimally invasive interventions
- Author
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Escoto, Abelardo, primary, Bhattad, Srikanth, additional, Shamsil, Arefin, additional, Sanches, Andre, additional, Trejos, Ana Luisa, additional, Naish, Michael D., additional, Malthaner, Richard A., additional, and Patel, Rajni V., additional
- Published
- 2015
- Full Text
- View/download PDF
19. Smart Rocking Armour Units
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Bas Hofland, Syed Shamsil Arefin, Cock van der Lem, and Marcel van Gent
- Subjects
Rocking ,gyroscope sensor ,concrete armour units ,rubble mound breakwater - Abstract
This paper describes a method to measure the rocking motion of lab-scale armour units. Sensors as found in mobile phones are used. These sensors, data-storage and battery are all embedded in the model units, such that they can be applied without wires attached to them. The technique is applied to double-layer units in order to compare the results to the existing knowledge for this type of armour layers. In contrast to previous research, the gyroscope reading is used to determine the (rocking) impact velocities. Two pioneer measurement series are described. From the readings both the temporal distribution of rocking can be inferred, as well as the spatial distribution. The temporal probability distribution for the rocking events seems logarithmic, with the impact velocity u2% being in the same order of magnitude as those reported earlier. These measurements indicate that for a randomly placed cube in an armour layer most rocking and most violent impact velocities occur about 2Dn under the waterline, instead of around the waterline. Moreover, the wave steepness is seen to have an effect on the rocking intensity. From the measurements with multiple units it can be seen that the measured impact velocity exhibits a large spatial variation among different units at an otherwise equal location.
20. A computational model for estimating tumor margins in complementary tactile and 3D ultrasound images
- Author
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Webster, Robert J., Yaniv, Ziv R., Shamsil, Arefin, Escoto, Abelardo, Naish, Michael D., and Patel, Rajni V.
- Published
- 2016
- Full Text
- View/download PDF
21. 2023 Canadian Surgery Forum: Sept. 20-23, 2023.
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Brière R, Émond M, Benhamed A, Blanchard PG, Drolet S, Habashi R, Golbon B, Shellenberger J, Pasternak J, Merchant S, Shellenberger J, La J, Sawhney M, Brogly S, Cadili L, Horkoff M, Ainslie S, Demetrick J, Chai B, Wiseman K, Hwang H, Alhumoud Z, Salem A, Lau R, Aw K, Nessim C, Gawad N, Alibhai K, Towaij C, Doan D, Raîche I, Valji R, Turner S, Balmes PN, Hwang H, Hameed SM, Tan JGK, Wijesuriya R, Tan JGK, Hew NLC, Wijesuriya R, Lund M, Hawel J, Gregor J, Leslie K, Lenet T, McIsaac D, Hallet J, Jerath A, Lalu M, Nicholls S, Presseau J, Tinmouth A, Verret M, Wherrett C, Fergusson D, Martel G, Sharma S, McKechnie T, Talwar G, Patel J, Heimann L, Doumouras A, Hong D, Eskicioglu C, Wang C, Guo M, Huang L, Sun S, Davis N, Wang J, Skulsky S, Sikora L, Raîche I, Son HJ, Gee D, Gomez D, Jung J, Selvam R, Seguin N, Zhang L, Lacaille-Ranger A, Sikora L, McIsaac D, Moloo H, Follett A, Holly, Organ M, Pace D, Balvardi S, Kaneva P, Semsar-Kazerooni K, Mueller C, Vassiliou M, Al Mahroos M, Fiore JF Jr, Schwartzman K, Feldman L, Guo M, Karimuddin A, Liu GP, Crump T, Sutherland J, Hickey K, Bonisteel EM, Umali J, Dogar I, Warden G, Boone D, Mathieson A, Hogan M, Pace D, Seguin N, Moloo H, Li Y, Best G, Leong R, Wiseman S, Alaoui AA, Hajjar R, Wassef E, Metellus DS, Dagbert F, Loungnarath R, Ratelle R, Schwenter F, Debroux É, Wassef R, Gagnon-Konamna M, Pomp A, Richard CS, Sebajang H, Alaoui AA, Hajjar R, Dagbert F, Loungnarath R, Sebajang H, Ratelle R, Schwenter F, Debroux É, Wassef R, Gagnon-Konamna M, Pomp A, Santos MM, Richard CS, Shi G, Leung R, Lim C, Knowles S, Parmar S, Wang C, Debru E, Mohamed F, Anakin M, Lee Y, Samarasinghe Y, Khamar J, Petrisor B, McKechnie T, Eskicioglu C, Yang I, Mughal HN, Bhugio M, Gok MA, Khan UA, Fernandes AR, Spence R, Porter G, Hoogerboord CM, Neumann K, Pillar M, Guo M, Manhas N, Melck A, Kazi T, McKechnie T, Jessani G, Heimann L, Lee Y, Hong D, Eskicioglu C, McKechnie T, Tessier L, Archer V, Park L, Cohen D, Parpia S, Bhandari M, Dionne J, Eskicioglu C, Bolin S, Afford R, Armstrong M, Karimuddin A, Leung R, Shi G, Lim C, Grant A, Van Koughnett JA, Knowles S, Clement E, Lange C, Roshan A, Karimuddin A, Scott T, Nadeau K, Macmillan J, Wilson J, Deschenes M, Nurullah A, Cahill C, Chen VH, Patterson KM, Wiseman SM, Wen B, Bhudial J, Barton A, Lie J, Park CM, Yang L, Gouskova N, Kim DH, Afford R, Bolin S, Morris-Janzen D, McLellan A, Karimuddin A, Archer V, Cloutier Z, Berg A, McKechnie T, Wiercioch W, Eskicioglu C, Labonté J, Bisson P, Bégin A, Cheng-Oviedo SG, Collin Y, Fernandes AR, Hossain I, Ellsmere J, El-Kefraoui C, Do U, Miller A, Kouyoumdjian A, Cui D, Khorasani E, Landry T, Amar-Zifkin A, Lee L, Feldman L, Fiore J, Au TM, Oppenheimer M, Logsetty S, AlShammari R, AlAbri M, Karimuddin A, Brown C, Raval MJ, Phang PT, Bird S, Baig Z, Abu-Omar N, Gill D, Suresh S, Ginther N, Karpinski M, Ghuman A, Malik PRA, Alibhai K, Zabolotniuk T, Raîche I, Gawad N, Mashal S, Boulanger N, Watt L, Razek T, Fata P, Grushka J, Wong EG, Hossain I, Landry M, Mackey S, Fairbridge N, Greene A, Borgoankar M, Kim C, DeCarvalho D, Pace D, Wigen R, Walser E, Davidson J, Dorward M, Muszynski L, Dann C, Seemann N, Lam J, Harding K, Lowik AJ, Guinard C, Wiseman S, Ma O, Mocanu V, Lin A, Karmali S, Bigam D, Harding K, Greaves G, Parker B, Nguyen V, Ahmed A, Yee B, Perren J, Norman M, Grey M, Perini R, Jowhari F, Bak A, Drung J, Allen L, Wiseman D, Moffat B, Lee JKH, McGuire C, Raîche I, Tudorache M, Gawad N, Park LJ, Borges FK, Nenshi R, Jacka M, Heels-Ansdell D, Simunovic M, Bogach J, Serrano PE, Thabane L, Devereaux PJ, Farooq S, Lester E, Kung J, Bradley N, Best G, Ahn S, Zhang L, Prince N, Cheng-Boivin O, Seguin N, Wang H, Quartermain L, Tan S, Shamess J, Simard M, Vigil H, Raîche I, Hanna M, Moloo H, Azam R, Ko G, Zhu M, Raveendran Y, Lam C, Tang J, Bajwa A, Englesakis M, Reel E, Cleland J, Snell L, Lorello G, Cil T, Ahn HS, Dube C, McIsaac D, Smith D, Leclerc A, Shamess J, Rostom A, Calo N, Thavorn K, Moloo H, Laplante S, Liu L, Khan N, Okrainec A, Ma O, Lin A, Mocanu V, Karmali S, Bigam D, Bruyninx G, Georgescu I, Khokhotva V, Talwar G, Sharma S, McKechnie T, Yang S, Khamar J, Hong D, Doumouras A, Eskicioglu C, Spoyalo K, Rebello TA, Chhipi-Shrestha G, Mayson K, Sadiq R, Hewage K, MacNeill A, Muncner S, Li MY, Mihajlovic I, Dykstra M, Snelgrove R, Wang H, Schweitzer C, Wiseman SM, Garcha I, Jogiat U, Baracos V, Turner SR, Eurich D, Filafilo H, Rouhi A, Bédard A, Bédard ELR, Patel YS, Alaichi JA, Agzarian J, Hanna WC, Patel YS, Alaichi JA, Provost E, Shayegan B, Adili A, Hanna WC, Mistry N, Gatti AA, Patel YS, Farrokhyar F, Xie F, Hanna WC, Sullivan KA, Farrokhyar F, Patel YS, Liberman M, Turner SR, Gonzalez AV, Nayak R, Yasufuku K, Hanna WC, Mistry N, Gatti AA, Patel YS, Cross S, Farrokhyar F, Xie F, Hanna WC, Haché PL, Galvaing G, Simard S, Grégoire J, Bussières J, Lacasse Y, Sassi S, Champagne C, Laliberté AS, Jeong JY, Jogiat U, Wilson H, Bédard A, Blakely P, Dang J, Sun W, Karmali S, Bédard ELR, Wong C, Hakim SY, Azizi S, El-Menyar A, Rizoli S, Al-Thani H, Fernandes AR, French D, Li C, Ellsmere J, Gossen S, French D, Bailey J, Tibbo P, Crocker C, Bondzi-Simpson A, Ribeiro T, Kidane B, Ko M, Coburn N, Kulkarni G, Hallet J, Ramzee AF, Afifi I, Alani M, El-Menyar A, Rizoli S, Al-Thani H, Chughtai T, Huo B, Manos D, Xu Z, Kontouli KM, Chun S, Fris J, Wallace AMR, French DG, Giffin C, Liberman M, Dayan G, Laliberté AS, Yasufuku K, Farivar A, Kidane B, Weessies C, Robinson M, Bednarek L, Buduhan G, Liu R, Tan L, Srinathan SK, Kidane B, Nasralla A, Safieddine N, Gazala S, Simone C, Ahmadi N, Hilzenrat R, Blitz M, Deen S, Humer M, Jugnauth A, Buduhan G, Kerr L, Sun S, Browne I, Patel Y, Hanna W, Loshusan B, Shamsil A, Naish MD, Qiabi M, Nayak R, Patel R, Malthaner R, Pooja P, Roberto R, Greg H, Daniel F, Huynh C, Sharma S, Vieira A, Jain F, Lee Y, Mousa-Doust D, Costa J, Mezei M, Chapman K, Briemberg H, Jack K, Grant K, Choi J, Yee J, McGuire AL, Abdul SA, Khazoom F, Aw K, Lau R, Gilbert S, Sundaresan S, Jones D, Seely AJE, Villeneuve PJ, Maziak DE, Pigeon CA, Frigault J, Drolet S, Roy ÈM, Bujold-Pitre K, Courval V, Tessier L, McKechnie T, Lee Y, Park L, Gangam N, Eskicioglu C, Cloutier Z, McKechnie T (McMaster University), Archer V, Park L, Lee J, Patel A, Hong D, Eskicioglu C, Ichhpuniani S, McKechnie T, Elder G, Chen A, Logie K, Doumouras A, Hong D, Benko R, Eskicioglu C, Castelo M, Paszat L, Hansen B, Scheer A, Faught N, Nguyen L, Baxter N, Sharma S, McKechnie T, Khamar J, Wu K, Eskicioglu C, McKechnie T, Khamar J, Lee Y, Tessier L, Passos E, Doumouras A, Hong D, Eskicioglu C, McKechnie T, Khamar J, Sachdeva A, Lee Y, Hong D, Eskicioglu C, Fei LYN, Caycedo A, Patel S, Popa T, Boudreau L, Grin A, Wang T, Lie J, Karimuddin A, Brown C, Phang T, Raval M, Ghuman A, Candy S, Nanda K, Li C, Snelgrove R, Dykstra M, Kroeker K, Wang H, Roy H, Helewa RM, Johnson G, Singh H, Hyun E, Moffatt D, Vergis A, Balmes P, Phang T, Guo M, Liu J, Roy H, Webber S, Shariff F, Helewa RM, Hochman D, Park J, Johnson G, Hyun E, Robitaille S, Wang A, Maalouf M, Alali N, Elhaj H, Liberman S, Charlebois P, Stein B, Feldman L, Fiore JF Jr, Lee L, Hu R, Lacaille-Ranger A, Ahn S, Tudorache M, Moloo H, Williams L, Raîche I, Musselman R, Lemke M, Allen L, Samarasinghe N, Vogt K, Brackstone M, Zwiep T, Clement E, Lange C, Alam A, Ghuman A, Karimuddin A, Phang T, Raval M, Brown C, Clement E, Liu J, Ghuman A, Karimuddin A, Phang T, Raval M, Brown C, Mughal HN, Gok MA, Khan UA, Mughal HN, Gok MA, Khan UA, Mughal HN, Gok MA, Khan UA, Mughal HN, Gok MA, Khan UA, James N, Zwiep T, Van Koughnett JA, Laczko D, McKechnie T, Yang S, Wu K, Sharma S, Lee Y, Park L, Doumouras A, Hong D, Parpia S, Bhandari M, Eskicioglu C, McKechnie T, Tessier L, Lee S, Kazi T, Sritharan P, Lee Y, Doumouras A, Hong D, Eskicioglu C, McKechnie T, Lee Y, Hong D, Dionne J, Doumouras A, Parpia S, Bhandari M, Eskicioglu C, Hershorn O, Ghuman A, Karimuddin A, Brown C, Raval M, Phang PT, Chen A, Boutros M, Caminsky N, Dumitra T, Faris-Sabboobeh S, Demian M, Rigas G, Monton O, Smith A, Moon J, Demian M, Garfinkle R, Vasilevsky CA, Rajabiyazdi F, Boutros M, Courage E, LeBlanc D, Benesch M, Hickey K, Hartwig K, Armstrong C, Engelbrecht R, Fagan M, Borgaonkar M, Pace D, Shanahan J, Moon J, Salama E, Wang A, Arsenault M, Leon N, Loiselle C, Rajabiyazdi F, Boutros M, Brennan K, Rai M, Farooq A, McClintock C, Kong W, Patel S, Boukhili N, Caminsky N, Faris-Sabboobeh S, Demian M, Boutros M, Paradis T, Robitaille S, Dumitra T, Liberman AS, Charlebois P, Stein B, Fiore JF Jr, Feldman LS, Lee L, Zwiep T, Abner D, Alam T, Beyer E, Evans M, Hill M, Johnston D, Lohnes K, Menard S, Pitcher N, Sair K, Smith B, Yarjau B, LeBlanc K, Samarasinghe N, Karimuddin AA, Brown CJ, Phang PT, Raval MJ, MacDonell K, Ghuman A, Harvey A, Phang PT, Karimuddin A, Brown CJ, Raval MJ, Ghuman A, Hershorn O, Ghuman A, Karimuddin A, Raval M, Phang PT, Brown C, Logie K, Mckechnie T, Lee Y, Hong D, Eskicioglu C, Matta M, Baker L, Hopkins J, Rochon R, Buie D, MacLean A, Ghuman A, Park J, Karimuddin AA, Phang PT, Raval MJ, Brown CJ, Farooq A, Ghuman A, Patel S, Macdonald H, Karimuddin A, Raval M, Phang PT, Brown C, Wiseman V, Brennan K, Patel S, Farooq A, Merchant S, Kong W, McClintock C, Booth C, Hann T, Ricci A, Patel S, Brennan K, Wiseman V, McClintock C, Kong W, Farooq A, Kakkar R, Hershorn O, Raval M, Phang PT, Karimuddin A, Ghuman A, Brown C, Wiseman V, Farooq A, Patel S, Hajjar R, Gonzalez E, Fragoso G, Oliero M, Alaoui AA, Rendos HV, Djediai S, Cuisiniere T, Laplante P, Gerkins C, Ajayi AS, Diop K, Taleb N, Thérien S, Schampaert F, Alratrout H, Dagbert F, Loungnarath R, Sebajang H, Schwenter F, Wassef R, Ratelle R, Debroux É, Cailhier JF, Routy B, Annabi B, Brereton NJB, Richard C, Santos MM, Gimon T, MacRae H, de Buck van Overstraeten A, Brar M, Chadi S, Kennedy E, Baker L, Hopkins J, Rochon R, Buie D, MacLean A, Park LJ, Archer V, McKechnie T, Lee Y, McIsaac D, Rashanov P, Eskicioglu C, Moloo H, 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- Published
- 2023
- Full Text
- View/download PDF
22. Texture-based Intraoperative Image Guidance for Tumor Localization in Minimally Invasive Surgery.
- Author
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Shamsil A, Naish MD, and Patel RV
- Subjects
- Feedback, Humans, Palpation, Touch, Minimally Invasive Surgical Procedures, Neoplasms
- Abstract
Intraoperative tumor localization in a deflated lung in minimally invasive surgery (MIS) is challenging as the lung cannot be manually palpated through small incisions. To do so remotely, an articulated multisensory imaging device combining tactile and ultrasound sensors was developed. It visualizes the surface tactile map and the depth of the tissue. However, with little maneuverability in MIS, localizing tumors using instrumented palpation is both tedious and inefficient. In this paper, a texture- based image guidance system that classifies tactile-guided ultrasound texture regions and provides beliefs on their types is proposed. The resulting interactive feedback allows directed palpation in MIS. A k-means classifier is used to first cluster gray-level co-occurrence matrix (GLCM)-based texture features of the ultrasound regions, followed by hidden Markov model-based belief propagation to establish confidence about the clustered features observing repeated patterns. When the beliefs converge, the system autonomously detects tumor and nontumor textures. The approach was tested on 20 ex vivo soft tissue specimens in a staged MIS. The results showed that with guidance, tumors in MIS could be localized with 98% accuracy, 99% sensitivity, and 97% specificity.Clinical Relevance- Texture-based image guidance adds efficiency and control to instrumented palpation in MIS. It renders fluidity and accuracy in image acquisition using a hand-held device where fatigue from prolonged handling affects imaging quality.
- Published
- 2021
- Full Text
- View/download PDF
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